{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T15:54:37Z","timestamp":1776095677051,"version":"3.50.1"},"reference-count":224,"publisher":"Association for Computing Machinery (ACM)","issue":"5","license":[{"start":{"date-parts":[[2020,8,17]],"date-time":"2020-08-17T00:00:00Z","timestamp":1597622400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Adapt Centre and Marie Sklodowska-Curie","award":["722022"],"award-info":[{"award-number":["722022"]}]},{"name":"SFI","award":["13\/RC\/2106"],"award-info":[{"award-number":["13\/RC\/2106"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Comput.-Hum. Interact."],"published-print":{"date-parts":[[2020,10,31]]},"abstract":"<jats:p>High prevalence of mental illness and the need for effective mental health care, combined with recent advances in AI, has led to an increase in explorations of how the field of machine learning (ML) can assist in the detection, diagnosis and treatment of mental health problems. ML techniques can potentially offer new routes for learning patterns of human behavior; identifying mental health symptoms and risk factors; developing predictions about disease progression; and personalizing and optimizing therapies. Despite the potential opportunities for using ML within mental health, this is an emerging research area, and the development of effective ML-enabled applications that are implementable in practice is bound up with an array of complex, interwoven challenges. Aiming to guide future research and identify new directions for advancing development in this important domain, this article presents an introduction to, and a systematic review of, current ML work regarding psycho-socially based mental health conditions from the computing and HCI literature. A quantitative synthesis and qualitative narrative review of 54 papers that were included in the analysis surfaced common trends, gaps, and challenges in this space. Discussing our findings, we (i) reflect on the current state-of-the-art of ML work for mental health, (ii) provide concrete suggestions for a stronger integration of human-centered and multi-disciplinary approaches in research and development, and (iii) invite more consideration of the potentially far-reaching personal, social, and ethical implications that ML models and interventions can have, if they are to find widespread, successful adoption in real-world mental health contexts.<\/jats:p>","DOI":"10.1145\/3398069","type":"journal-article","created":{"date-parts":[[2020,7,7]],"date-time":"2020-07-07T12:34:24Z","timestamp":1594125264000},"page":"1-53","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":336,"title":["Machine Learning in Mental Health"],"prefix":"10.1145","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9639-5531","authenticated-orcid":false,"given":"Anja","family":"Thieme","sequence":"first","affiliation":[{"name":"Microsoft Research, Cambridge, Cambridgeshire, UK"}]},{"given":"Danielle","family":"Belgrave","sequence":"additional","affiliation":[{"name":"Microsoft Research, Cambridge, Cambridgeshire, UK"}]},{"given":"Gavin","family":"Doherty","sequence":"additional","affiliation":[{"name":"Trinity College Dublin, College Green, Dublin"}]}],"member":"320","published-online":{"date-parts":[[2020,8,17]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3174156"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3200947.3201020"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2794470"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/967900.967960"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2014.583"},{"key":"e_1_2_1_6_1","volume-title":"Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication (ICUIMC\u201914)","unstructured":"Md. Golam Rabiul Alam, Eung Jun Cho, Eui-Nam Huh, and Choong Seon Hong. 2014. Cloud based mental state monitoring system for suicide risk reconnaissance using wearable bio-sensors . In Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication (ICUIMC\u201914) . ACM, Paper 56, 6 pages. DOI:https:\/\/doi.org\/10.1145\/2557977.2558020 10.1145\/2557977.2558020 Md. Golam Rabiul Alam, Eung Jun Cho, Eui-Nam Huh, and Choong Seon Hong. 2014. Cloud based mental state monitoring system for suicide risk reconnaissance using wearable bio-sensors. In Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication (ICUIMC\u201914). ACM, Paper 56, 6 pages. DOI:https:\/\/doi.org\/10.1145\/2557977.2558020"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v35i4.2513"},{"key":"e_1_2_1_8_1","volume-title":"Diagnostic and Statistical Manual of Mental Disorders (DSM--5). Last retrieved 7 th","author":"American Psychiatry Association","year":"2019","unstructured":"American Psychiatry Association . 2019. Diagnostic and Statistical Manual of Mental Disorders (DSM--5). Last retrieved 7 th July 2019 from https:\/\/www.psychiatry.org\/psychiatrists\/practice\/dsm. American Psychiatry Association. 2019. Diagnostic and Statistical Manual of Mental Disorders (DSM--5). Last retrieved 7 th July 2019 from https:\/\/www.psychiatry.org\/psychiatrists\/practice\/dsm."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0749-3797(18)30622-6"},{"key":"e_1_2_1_10_1","volume-title":"Calhoun","author":"Arbabshirani Mohammad R.","year":"2017","unstructured":"Mohammad R. Arbabshirani , Sergey Plis , Jing Sui , and Vince D . Calhoun . 2017 . Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. Neuroimage 145, PT B ( 2017), 137--165. DOI:https:\/\/doi.org\/10.1016\/j.neuroimage.2016.02.079 10.1016\/j.neuroimage.2016.02.079 Mohammad R. Arbabshirani, Sergey Plis, Jing Sui, and Vince D. Calhoun. 2017. Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. Neuroimage 145, PT B (2017), 137--165. DOI:https:\/\/doi.org\/10.1016\/j.neuroimage.2016.02.079"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3329189.3329248"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2470654.2481364"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.evalprogplan.2004.04.011"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209811.3209869"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1207\/S15327051HCI16234_05"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1037\/tra0000045"},{"key":"e_1_2_1_17_1","series-title":"Chapter 3","volume-title":"Principles of Contextual Inquiry","author":"Beyer Hugh","unstructured":"Hugh Beyer , and Karen Holtzblatt . 1997. Contextual design: Defining customer-centered systems . In Principles of Contextual Inquiry ( Chapter 3 ) . Elsevier , 41--66. Hugh Beyer, and Karen Holtzblatt. 1997. Contextual design: Defining customer-centered systems. In Principles of Contextual Inquiry (Chapter 3). Elsevier, 41--66."},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.14778\/3236187.3236217"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3291383"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2718581"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/805"},{"key":"e_1_2_1_22_1","volume-title":"Random Forests-Classification Description. Department of Statistics","author":"Breiman Leo","unstructured":"Leo Breiman and Adele Cutler . 2007. Random Forests-Classification Description. Department of Statistics , University of California , Berkeley. Leo Breiman and Adele Cutler. 2007. Random Forests-Classification Description. Department of Statistics, University of California, Berkeley."},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00779-011-0468-z"},{"key":"e_1_2_1_24_1","volume-title":"Proceedings of the Conference on Fairness, Accountability and Transparency (FAT\u201918)","author":"Buolamwini Joy","year":"2018","unstructured":"Joy Buolamwini , and Timnit Gebru . 2018 . Gender shades: Intersectional accuracy disparities in commercial gender classification . In Proceedings of the Conference on Fairness, Accountability and Transparency (FAT\u201918) . 77--91. Joy Buolamwini, and Timnit Gebru. 2018. Gender shades: Intersectional accuracy disparities in commercial gender classification. In Proceedings of the Conference on Fairness, Accountability and Transparency (FAT\u201918). 77--91."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bpsc.2017.11.007"},{"key":"e_1_2_1_26_1","volume-title":"Data Mining for Business Applications","author":"Cao Longbing","unstructured":"Longbing Cao , Philip S. Yu , Chengqi Zhang , and Huaifeng Zhang . 2008. Data Mining for Business Applications ( 1 st ed.). Springer Publishing Company, Inc orporated. Longbing Cao, Philip S. Yu, Chengqi Zhang, and Huaifeng Zhang. 2008. Data Mining for Business Applications (1st ed.). Springer Publishing Company, Incorporated.","edition":"1"},{"key":"e_1_2_1_27_1","volume-title":"Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD\u201917)","author":"Cao Bokai","unstructured":"Bokai Cao , Lei Zheng , Chenwei Zhang , Philip S. Yu , Andrea Piscitello , John Zulueta , Olu Ajilore , Kelly Ryan , and Alex D. Leow . 2017. DeepMood: Modeling mobile phone typing dynamics for mood detection . In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD\u201917) . ACM, 747--755. DOI:https:\/\/doi.org\/10.1145\/3097983.3098086 10.1145\/3097983.3098086 Bokai Cao, Lei Zheng, Chenwei Zhang, Philip S. Yu, Andrea Piscitello, John Zulueta, Olu Ajilore, Kelly Ryan, and Alex D. Leow. 2017. DeepMood: Modeling mobile phone typing dynamics for mood detection. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD\u201917). ACM, 747--755. DOI:https:\/\/doi.org\/10.1145\/3097983.3098086"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3170427.3173021"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3287560.3287587"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3359249"},{"key":"e_1_2_1_31_1","volume-title":"Proceedings of the CHI\u201911 Extended Abstracts on Human Factors in Computing Systems (CHI EA\u201911)","author":"Chan Matthew K.","year":"2011","unstructured":"Keng-hao Chang, Matthew K. Chan , and John Canny . 2011 . AnalyzeThis: Unobtrusive mental health monitoring by voice . In Proceedings of the CHI\u201911 Extended Abstracts on Human Factors in Computing Systems (CHI EA\u201911) . ACM, 1951--1956. DOI:https:\/\/doi.org\/10.1145\/1979742.1979859 10.1145\/1979742.1979859 Keng-hao Chang, Matthew K. Chan, and John Canny. 2011. AnalyzeThis: Unobtrusive mental health monitoring by voice. In Proceedings of the CHI\u201911 Extended Abstracts on Human Factors in Computing Systems (CHI EA\u201911). ACM, 1951--1956. DOI:https:\/\/doi.org\/10.1145\/1979742.1979859"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1504\/IJDATS.2017.086630"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3184558.3191624"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376341"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1748-720X.2002.tb00384.x"},{"key":"e_1_2_1_36_1","volume-title":"Baker","author":"Cipresso Pietro","year":"2018","unstructured":"Pietro Cipresso , Silvia Serino , Yuri Ostrovsky , and Justin T . Baker . 2018 . Pervasive computing paradigms for mental health. In Proceedings of the 7th International Conference, Mindcare 2018 ( 1 st ed.). Springer Publishing Company , Incorporated. Pietro Cipresso, Silvia Serino, Yuri Ostrovsky, and Justin T. Baker. 2018. Pervasive computing paradigms for mental health. In Proceedings of the 7th International Conference, Mindcare 2018 (1st ed.). Springer Publishing Company, Incorporated.","edition":"1"},{"key":"e_1_2_1_37_1","volume-title":"Proceedings of the s Neural Information Processing Systems (NIPS\u201917)","author":"Cisse Moustapha M.","year":"2017","unstructured":"Moustapha M. Cisse , Yossi Adi , Natalia Neverova , and Joseph Keshet . 2017 . Houdini: Fooling deep structured visual and speech recognition mossdels with adversarial examples . In Proceedings of the s Neural Information Processing Systems (NIPS\u201917) . 6977--6987. Moustapha M. Cisse, Yossi Adi, Natalia Neverova, and Joseph Keshet. 2017. Houdini: Fooling deep structured visual and speech recognition mossdels with adversarial examples. In Proceedings of the s Neural Information Processing Systems (NIPS\u201917). 6977--6987."},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.2307\/2136404"},{"key":"e_1_2_1_39_1","volume-title":"Rodell","author":"Colquitt Jason A.","year":"2015","unstructured":"Jason A. Colquitt , and Jessica B . Rodell . 2015 . Measuring justice and fairness. In Oxford Handbook of Justice in the Workplace. Vol. 187 , Oxford University Press , 202. Jason A. Colquitt, and Jessica B. Rodell. 2015. Measuring justice and fairness. In Oxford Handbook of Justice in the Workplace. Vol. 187, Oxford University Press, 202."},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W16-0311"},{"key":"e_1_2_1_41_1","article-title":"Emotional wellbeing","volume":"8","author":"Coyle David","year":"2014","unstructured":"David Coyle , Anja Thieme , Conor Linehan , Madeline Balaam , Jayne Wallace , and Si\u00e2n Lindley . 2014 . Emotional wellbeing . International Journal of Human Computer Studies 8 , 72 (2014), 627\u2212628. DOI:http:\/\/dx.doi.org\/10.1016\/j.ijhcs.2014.05.008 10.1016\/j.ijhcs.2014.05.008 David Coyle, Anja Thieme, Conor Linehan, Madeline Balaam, Jayne Wallace, and Si\u00e2n Lindley. 2014. Emotional wellbeing. International Journal of Human Computer Studies 8, 72 (2014), 627\u2212628. DOI:http:\/\/dx.doi.org\/10.1016\/j.ijhcs.2014.05.008","journal-title":"International Journal of Human Computer Studies"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/2858036.2858207"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/1276958.1277331"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123024.3125609"},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2006.04.007"},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11205-009-9493-y"},{"key":"e_1_2_1_47_1","volume-title":"Nadel","author":"Dipietro Loretta","year":"1993","unstructured":"Loretta Dipietro , Carl J. Caspersen , Adrian M. Ostfeld , and Ethan R . Nadel . 1993 . A survey for assessing physical activity among older adults. Medicine 8 Science in Sports 8 Exercise 25, 5 (1993), 628--642. DOI:http:\/\/dx.doi.org\/10.1249\/00005768-199305000-00016 10.1249\/00005768-199305000-00016 Loretta Dipietro, Carl J. Caspersen, Adrian M. Ostfeld, and Ethan R. Nadel. 1993. A survey for assessing physical activity among older adults. Medicine 8 Science in Sports 8 Exercise 25, 5 (1993), 628--642. DOI:http:\/\/dx.doi.org\/10.1249\/00005768-199305000-00016"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300416"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/2207676.2208602"},{"key":"e_1_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00779-014-0826-8"},{"key":"e_1_2_1_51_1","volume-title":"How to select the right evaluation metric for machine learning models: Part 1 regression metrics. Towards Data Science. Last retrieved 6th of","author":"Drakos Georgios","year":"2019","unstructured":"Georgios Drakos . 2018. How to select the right evaluation metric for machine learning models: Part 1 regression metrics. Towards Data Science. Last retrieved 6th of July 2019 from https:\/\/towardsdatascience.com\/how-to-select-the-right-evaluation-metric-for-machine-learning-models-part-1-regrression-metrics-3606e25beae0. Georgios Drakos. 2018. How to select the right evaluation metric for machine learning models: Part 1 regression metrics. Towards Data Science. Last retrieved 6th of July 2019 from https:\/\/towardsdatascience.com\/how-to-select-the-right-evaluation-metric-for-machine-learning-models-part-1-regrression-metrics-3606e25beae0."},{"key":"e_1_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3172944.3172961"},{"key":"e_1_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300364"},{"key":"e_1_2_1_54_1","volume-title":"Proceedings of the 4th International Conference on Neural Information Processing Systems (NIPS\u201991)","author":"Emad","unstructured":"Emad N. Eskandar and Barry J. Richmond. 1991. Decoding of neuronal signals in visual pattern recognition . In Proceedings of the 4th International Conference on Neural Information Processing Systems (NIPS\u201991) . J. E. Moody, S. J. Hanson, and R. P. Lippmann (Eds.), Morgan Kaufmann Publishers Inc., San Francisco, CA, 356--363. Emad N. Eskandar and Barry J. Richmond. 1991. Decoding of neuronal signals in visual pattern recognition. In Proceedings of the 4th International Conference on Neural Information Processing Systems (NIPS\u201991). J. E. Moody, S. J. Hanson, and R. P. Lippmann (Eds.), Morgan Kaufmann Publishers Inc., San Francisco, CA, 356--363."},{"key":"e_1_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3089341"},{"key":"e_1_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1002\/wps.20297"},{"key":"e_1_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1177\/0165551517740835"},{"key":"e_1_2_1_58_1","volume-title":"Participant","author":"Fiesler Casey","year":"2018","unstructured":"Casey Fiesler , and Nicholas Proferes . 2018. \u201c Participant \u201d perceptions of Twitter research ethics. Social Media + Society 4, 1 ( 2018 ), 1--14. DOI:https:\/\/doi.org\/10.1177%2F2056305118763366 Casey Fiesler, and Nicholas Proferes. 2018. \u201cParticipant\u201d perceptions of Twitter research ethics. Social Media + Society 4, 1 (2018), 1--14. DOI:https:\/\/doi.org\/10.1177%2F2056305118763366"},{"key":"e_1_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.5555\/1343031.1343035"},{"key":"e_1_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.5898\/JHRI.1.1.Feil-Seifer"},{"key":"e_1_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1145\/3194480.3194508"},{"key":"e_1_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/3347444.3356238"},{"key":"e_1_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1145\/2797143.2797159"},{"key":"e_1_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271732"},{"key":"e_1_2_1_65_1","volume-title":"Beam, and Rajesh Ranganath","author":"Ghassemi Marzyeh","year":"2018","unstructured":"Marzyeh Ghassemi , Tristan Naumann , Peter Schulam , Andrew L. Beam, and Rajesh Ranganath . 2018 . Opportunities in machine learning for healthcare. arXiv:1806.00388. DOI:https:\/\/arxiv.org\/abs\/1806.00388 Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L. Beam, and Rajesh Ranganath. 2018. Opportunities in machine learning for healthcare. arXiv:1806.00388. DOI:https:\/\/arxiv.org\/abs\/1806.00388"},{"key":"e_1_2_1_66_1","volume-title":"Hanna Wallach, Hal Daume\u00e9 III, and Kate Crawford.","author":"Gebru Timnit","year":"2018","unstructured":"Timnit Gebru , Jamie Morgenstern , Briana Vecchione , Jennifer Wortman Vaughan , Hanna Wallach, Hal Daume\u00e9 III, and Kate Crawford. 2018 . Datasheets for datasets. arXiv:1803.09010. DOI:https:\/\/arxiv.org\/abs\/1803.09010 Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daume\u00e9 III, and Kate Crawford. 2018. Datasheets for datasets. arXiv:1803.09010. DOI:https:\/\/arxiv.org\/abs\/1803.09010"},{"key":"e_1_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/2968219.2968306"},{"key":"e_1_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.2105\/AJPH.2012.300755"},{"key":"e_1_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0899-3467(07)60142-6"},{"key":"e_1_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.2196\/11696"},{"key":"e_1_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0307752101"},{"key":"e_1_2_1_72_1","first-page":"10","article-title":"Ranking neurons for mining structure-activity relations in biological neural networks","volume":"70","author":"G\u00fcrel Tayfun","year":"2007","unstructured":"Tayfun G\u00fcrel , Luc De Raedt , and Stefan Rotter . 2007 . Ranking neurons for mining structure-activity relations in biological neural networks : NeuronRank. Neurocomputing 70 , 10 -- 12 (2007), 1897--1901. DOI:http:\/\/dx.doi.org\/10.1016\/j.neucom.2006.10.064 10.1016\/j.neucom.2006.10.064 Tayfun G\u00fcrel, Luc De Raedt, and Stefan Rotter. 2007. Ranking neurons for mining structure-activity relations in biological neural networks: NeuronRank. Neurocomputing 70, 10--12 (2007), 1897--1901. DOI:http:\/\/dx.doi.org\/10.1016\/j.neucom.2006.10.064","journal-title":"NeuronRank. Neurocomputing"},{"key":"e_1_2_1_73_1","volume-title":"Hanna Wallach, and Meredith Ringel Morris.","author":"Guo Anhong","year":"2020","unstructured":"Anhong Guo , Ece Kamar , Jennifer Wortman Vaughan , Hanna Wallach, and Meredith Ringel Morris. 2020 . Toward fairness in AI for people with disabilities: A research roadmap. SIGACCESS Access. Comput. 125, Article 2 (October 2019), 1 page. DOI:https:\/\/doi.org\/10.1145\/3386296.3386298 10.1145\/3386296.3386298 Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna Wallach, and Meredith Ringel Morris. 2020. Toward fairness in AI for people with disabilities: A research roadmap. SIGACCESS Access. Comput. 125, Article 2 (October 2019), 1 page. DOI:https:\/\/doi.org\/10.1145\/3386296.3386298"},{"key":"e_1_2_1_74_1","unstructured":"Chuan Guo Mayank Rana Moustapha Cisse and Laurens Van Der Maaten. 2017. Countering adversarial images using input transformations. arXiv:1711.00117. DOI:https:\/\/arxiv.org\/abs\/1711.00117  Chuan Guo Mayank Rana Moustapha Cisse and Laurens Van Der Maaten. 2017. Countering adversarial images using input transformations. arXiv:1711.00117. DOI:https:\/\/arxiv.org\/abs\/1711.00117"},{"key":"e_1_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2008.12.002"},{"key":"e_1_2_1_76_1","unstructured":"Hoda Heidari Claudio Ferrari Krishna P. Gummadi and Andreas Krause. 2018. Fairness behind a veil of ignorance: A welfare analysis for automated decision making. arXiv:1806.04959. DOI:https:\/\/arxiv.org\/abs\/1806.04959  Hoda Heidari Claudio Ferrari Krishna P. Gummadi and Andreas Krause. 2018. Fairness behind a veil of ignorance: A welfare analysis for automated decision making. arXiv:1806.04959. DOI:https:\/\/arxiv.org\/abs\/1806.04959"},{"key":"e_1_2_1_77_1","volume-title":"Proceedings of the 2017 Conference on Designing Interactive Systems (DIS\u201917)","author":"Hirsch Tad","unstructured":"Tad Hirsch , Kritzia Merced , Shrikanth Narayanan , Zac E. Imel , and David C. Atkins . 2017. Designing contestability: Interaction design, machine learning, and mental health . In Proceedings of the 2017 Conference on Designing Interactive Systems (DIS\u201917) . ACM, 95--99. DOI:https:\/\/doi.org\/10.1145\/3064663.3064703 10.1145\/3064663.3064703 Tad Hirsch, Kritzia Merced, Shrikanth Narayanan, Zac E. Imel, and David C. Atkins. 2017. Designing contestability: Interaction design, machine learning, and mental health. In Proceedings of the 2017 Conference on Designing Interactive Systems (DIS\u201917). ACM, 95--99. DOI:https:\/\/doi.org\/10.1145\/3064663.3064703"},{"key":"e_1_2_1_78_1","volume-title":"Automated Evaluation. In Proceedings of the 2018 Designing Interactive Systems Conference (DIS\u201918)","author":"Hirsch Tad","year":"1967","unstructured":"Tad Hirsch , Christina Soma , Kritzia Merced , Patty Kuo , Aaron Dembe , Derek D. Caperton , David C. Atkins , and Zac E. Imel . 2018. \u201cIt's hard to argue with a computer\u201d: Investigating Psychotherapists\u2019 Attitudes towards Automated Evaluation. In Proceedings of the 2018 Designing Interactive Systems Conference (DIS\u201918) . ACM, 559--571. DOI:https:\/\/doi.org\/10.1145\/3 1967 09.3196776 10.1145\/3196709.3196776 Tad Hirsch, Christina Soma, Kritzia Merced, Patty Kuo, Aaron Dembe, Derek D. Caperton, David C. Atkins, and Zac E. Imel. 2018. \u201cIt's hard to argue with a computer\u201d: Investigating Psychotherapists\u2019 Attitudes towards Automated Evaluation. In Proceedings of the 2018 Designing Interactive Systems Conference (DIS\u201918). ACM, 559--571. DOI:https:\/\/doi.org\/10.1145\/3196709.3196776"},{"key":"e_1_2_1_79_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0953-5438(99)00006-5"},{"key":"e_1_2_1_80_1","doi-asserted-by":"publisher","DOI":"10.1109\/ARSO.2017.8025197"},{"key":"e_1_2_1_81_1","volume-title":"Proceedings of the 7th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP\u201910)","author":"Jagadeesh Vignesh","year":"1924","unstructured":"Vignesh Jagadeesh , S. Karthikeyan , and B. S. Manjunath . 2010. Spatio-temporal optical flow statistics (STOFS) for activity classification . In Proceedings of the 7th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP\u201910) . ACM, 178--182. DOI:http:\/\/dx.doi.org\/10.1145\/ 1924 559.1924583 10.1145\/1924559.1924583 Vignesh Jagadeesh, S. Karthikeyan, and B. S. Manjunath. 2010. Spatio-temporal optical flow statistics (STOFS) for activity classification. In Proceedings of the 7th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP\u201910). ACM, 178--182. DOI:http:\/\/dx.doi.org\/10.1145\/1924559.1924583"},{"key":"e_1_2_1_82_1","doi-asserted-by":"publisher","DOI":"10.1145\/3027063.3048417"},{"key":"e_1_2_1_83_1","volume-title":"Proceedings of the NIPS Workshop on Machine Learning for Healthcare. Last Retrieved 14th","author":"Jaques Natasha","year":"2016","unstructured":"Natasha Jaques , Sara Taylor , Ehimwenma Nosakhare , Akane Sano , and Rosalind Picard . 2016 . Multi-task learning for predicting health, stress, and happiness . In Proceedings of the NIPS Workshop on Machine Learning for Healthcare. Last Retrieved 14th September 2019 from https:\/\/pdfs.semanticscholar.org\/b228\/7a406985980515d5cc63e9b37fb17c5186f8.pdf. Natasha Jaques, Sara Taylor, Ehimwenma Nosakhare, Akane Sano, and Rosalind Picard. 2016. Multi-task learning for predicting health, stress, and happiness. In Proceedings of the NIPS Workshop on Machine Learning for Healthcare. Last Retrieved 14th September 2019 from https:\/\/pdfs.semanticscholar.org\/b228\/7a406985980515d5cc63e9b37fb17c5186f8.pdf."},{"key":"e_1_2_1_84_1","doi-asserted-by":"publisher","DOI":"10.1145\/2974804.2974831"},{"key":"e_1_2_1_85_1","volume-title":"Mitchell","author":"Jordan Michael I.","year":"2015","unstructured":"Michael I. Jordan , and Tom M . Mitchell . 2015 . Machine learning: Trends, perspectives, and prospects. Science 349, 6245 (2015), 255--260. DOI:https:\/\/doi.org\/10.1126\/science.aaa8415 10.1126\/science.aaa8415 Michael I. Jordan, and Tom M. Mitchell. 2015. Machine learning: Trends, perspectives, and prospects. Science 349, 6245 (2015), 255--260. DOI:https:\/\/doi.org\/10.1126\/science.aaa8415"},{"key":"e_1_2_1_86_1","volume-title":"Proceedings of the ACM India Joint International Conference on Data Science and Management of Data (CoDS-COMAD\u201918)","author":"Joshi Deepali J.","unstructured":"Deepali J. Joshi , Mohit Makhija , Yash Nabar , Ninad Nehete , and Manasi S. Patwardhan . 2018. Mental health analysis using deep learning for feature extraction . In Proceedings of the ACM India Joint International Conference on Data Science and Management of Data (CoDS-COMAD\u201918) . 356--359. DOI:https:\/\/doi.org\/10.1145\/3152494.3167990 10.1145\/3152494.3167990 Deepali J. Joshi, Mohit Makhija, Yash Nabar, Ninad Nehete, and Manasi S. Patwardhan. 2018. Mental health analysis using deep learning for feature extraction. In Proceedings of the ACM India Joint International Conference on Data Science and Management of Data (CoDS-COMAD\u201918). 356--359. DOI:https:\/\/doi.org\/10.1145\/3152494.3167990"},{"key":"e_1_2_1_87_1","doi-asserted-by":"publisher","DOI":"10.1109\/CBMS.2010.6042686"},{"key":"e_1_2_1_88_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-019-7327-8"},{"key":"e_1_2_1_89_1","doi-asserted-by":"publisher","DOI":"10.1145\/2975167.2975170"},{"key":"e_1_2_1_90_1","first-page":"168","article-title":"Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization's World Mental Health Survey Initiative","volume":"6","author":"Kessler Ronald C.","year":"2007","unstructured":"Ronald C. Kessler 2007 . Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization's World Mental Health Survey Initiative . World Psychiatry 6 , 3 (2007), 168 . DOI: s Ronald C. Kessler et al. 2007. Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization's World Mental Health Survey Initiative. World Psychiatry 6, 3 (2007), 168. DOI: s","journal-title":"World Psychiatry"},{"key":"e_1_2_1_91_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.2008.08010126"},{"key":"e_1_2_1_92_1","volume-title":"Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB\u201918)","author":"Alex","unstructured":"Alex V. Kotlar and Thomas S. Wingo. 2018. Tutorial: Rapidly Identifying Disease-associated Rare Variants using Annotation and Machine Learning at Whole-genome Scale Online . In Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB\u201918) . ACM, 558--558. DOI:https:\/\/doi.org\/10.1145\/3233547.3233666 10.1145\/3233547.3233666 Alex V. Kotlar and Thomas S. Wingo. 2018. Tutorial: Rapidly Identifying Disease-associated Rare Variants using Annotation and Machine Learning at Whole-genome Scale Online. In Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB\u201918). ACM, 558--558. DOI:https:\/\/doi.org\/10.1145\/3233547.3233666"},{"key":"e_1_2_1_93_1","volume-title":"Keane","author":"Koza John R.","year":"1996","unstructured":"John R. Koza , Forrest H. Bennett , David Andre , and Martin A . Keane . 1996 . Automated design of both the topology and sizing of analog electrical circuits using genetic programming. In Proceedings of the Artificial Intelligence in Design\u201996. Springer , 151--170. DOI:https:\/\/doi.org\/10.1007\/978-94-009-0279-4_9 10.1007\/978-94-009-0279-4_9 John R. Koza, Forrest H. Bennett, David Andre, and Martin A. Keane. 1996. Automated design of both the topology and sizing of analog electrical circuits using genetic programming. In Proceedings of the Artificial Intelligence in Design\u201996. Springer, 151--170. DOI:https:\/\/doi.org\/10.1007\/978-94-009-0279-4_9"},{"key":"e_1_2_1_94_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2006.10.130"},{"key":"e_1_2_1_95_1","doi-asserted-by":"publisher","DOI":"10.1002\/ima.20166"},{"key":"e_1_2_1_96_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2008.02-07-474"},{"key":"e_1_2_1_97_1","doi-asserted-by":"publisher","DOI":"10.3928\/0048-5713-20020901-06"},{"key":"e_1_2_1_98_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2008.20.1.1"},{"key":"e_1_2_1_99_1","doi-asserted-by":"publisher","DOI":"10.1145\/3301421"},{"key":"e_1_2_1_100_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2018.08.073"},{"key":"e_1_2_1_101_1","doi-asserted-by":"publisher","DOI":"10.1145\/2508037.2508052"},{"key":"e_1_2_1_102_1","doi-asserted-by":"publisher","DOI":"10.1145\/3359284"},{"key":"e_1_2_1_103_1","doi-asserted-by":"publisher","DOI":"10.1162\/089976604323057407"},{"key":"e_1_2_1_104_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1000100"},{"key":"e_1_2_1_105_1","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654945"},{"key":"e_1_2_1_106_1","doi-asserted-by":"publisher","DOI":"10.1145\/3236386.3241340"},{"key":"e_1_2_1_107_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290607.3299081"},{"key":"e_1_2_1_108_1","volume-title":"S","author":"Liu Zengjian","year":"2017","unstructured":"Zengjian Liu , Buzhou Tang , Xiaolong Wang , and Qingcai Chen . 2017. De-identification of clinical notes via recurrent neural network and conditional random field. Journal of Biomedical Informatics 75 , S ( 2017 ), S34--S42. DOI:https:\/\/doi.org\/10.1016\/j.jbi.2017.05.023 10.1016\/j.jbi.2017.05.023 Zengjian Liu, Buzhou Tang, Xiaolong Wang, and Qingcai Chen. 2017. De-identification of clinical notes via recurrent neural network and conditional random field. Journal of Biomedical Informatics 75, S (2017), S34--S42. DOI:https:\/\/doi.org\/10.1016\/j.jbi.2017.05.023"},{"key":"e_1_2_1_109_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-41959-6_11"},{"key":"e_1_2_1_110_1","doi-asserted-by":"publisher","DOI":"10.1145\/1864349.1864394"},{"key":"e_1_2_1_111_1","volume-title":"Proceedings of the 11th Australasian Conference on Information Systems.","volume":"53","author":"Madsen Maria","year":"2000","unstructured":"Maria Madsen , and Shirley Gregor . 2000 . Measuring human-computer trust . In Proceedings of the 11th Australasian Conference on Information Systems. Vol. 53 , 6--8. Maria Madsen, and Shirley Gregor. 2000. Measuring human-computer trust. In Proceedings of the 11th Australasian Conference on Information Systems. Vol. 53, 6--8."},{"key":"e_1_2_1_112_1","volume-title":"Proceedings of the 20th ACM International Conference on Multimodal Interaction (ICMI\u201918)","author":"Mallol-Ragolta Adria","unstructured":"Adria Mallol-Ragolta , Svati Dhamija , and Terrance E. Boult . 2018. A multimodal approach for predicting changes in PTSD symptom severity . In Proceedings of the 20th ACM International Conference on Multimodal Interaction (ICMI\u201918) . ACM, 324--333. DOI:https:\/\/doi.org\/10.1145\/3242969.3242981 10.1145\/3242969.3242981 Adria Mallol-Ragolta, Svati Dhamija, and Terrance E. Boult. 2018. A multimodal approach for predicting changes in PTSD symptom severity. In Proceedings of the 20th ACM International Conference on Multimodal Interaction (ICMI\u201918). ACM, 324--333. DOI:https:\/\/doi.org\/10.1145\/3242969.3242981"},{"key":"e_1_2_1_113_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-017-0760-1"},{"key":"#cr-split#-e_1_2_1_114_1.1","doi-asserted-by":"crossref","unstructured":"Martin Maritsch Caterina B\u00e9rub\u00e9 Mathias Kraus Vera Lehmann Thomas Z\u00fcger Stefan Feuerriegel Tobias Kowatsch and Felix Wortmann. 2019. Improving heart rate variability measurements from consumer smartwatches with machine learning. In Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers (UbiComp\/ISWC'19 Adjunct). ACM 934--938. DOI:https:\/\/doi.org\/10.1145\/3341162.3346276 10.1145\/3341162.3346276","DOI":"10.1145\/3341162.3346276"},{"key":"#cr-split#-e_1_2_1_114_1.2","doi-asserted-by":"crossref","unstructured":"Martin Maritsch Caterina B\u00e9rub\u00e9 Mathias Kraus Vera Lehmann Thomas Z\u00fcger Stefan Feuerriegel Tobias Kowatsch and Felix Wortmann. 2019. Improving heart rate variability measurements from consumer smartwatches with machine learning. In Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers (UbiComp\/ISWC'19 Adjunct). ACM 934--938. DOI:https:\/\/doi.org\/10.1145\/3341162.3346276","DOI":"10.1145\/3341162.3346276"},{"key":"e_1_2_1_115_1","doi-asserted-by":"publisher","DOI":"10.1145\/3300061.3300141"},{"key":"e_1_2_1_116_1","doi-asserted-by":"publisher","DOI":"10.1016\/S2215-0366(16)30089-X"},{"key":"e_1_2_1_117_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098075"},{"key":"e_1_2_1_118_1","doi-asserted-by":"publisher","DOI":"10.1145\/3089341.3089342"},{"key":"e_1_2_1_119_1","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.7126"},{"key":"e_1_2_1_120_1","doi-asserted-by":"publisher","DOI":"10.1145\/3325426.3329948"},{"key":"e_1_2_1_121_1","volume-title":"Version 2.1","author":"Miller William R.","unstructured":"William R. Miller , Theresa B. Moyers , Denise Ernst , and Paul Amrhein . 2003. Manual for the Motivational Interviewing Skill Code (MISC) , Version 2.1 . Center on Alcoholism, Substance Abuse and Addictions, University of New Mexico . Last retrieved 14th of September from https:\/\/casaa.unm.edu\/download\/misc.pdf. William R. Miller, Theresa B. Moyers, Denise Ernst, and Paul Amrhein. 2003. Manual for the Motivational Interviewing Skill Code (MISC), Version 2.1. Center on Alcoholism, Substance Abuse and Addictions, University of New Mexico. Last retrieved 14th of September from https:\/\/casaa.unm.edu\/download\/misc.pdf."},{"key":"e_1_2_1_122_1","doi-asserted-by":"publisher","DOI":"10.1145\/2661806.2661818"},{"key":"e_1_2_1_123_1","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-151-4-200908180-00135"},{"key":"e_1_2_1_124_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-clinpsy-032816-044949"},{"key":"e_1_2_1_125_1","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.6645"},{"key":"e_1_2_1_126_1","doi-asserted-by":"publisher","DOI":"10.1192\/bjp.134.4.382"},{"key":"e_1_2_1_127_1","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.3575"},{"key":"e_1_2_1_128_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351233"},{"key":"e_1_2_1_129_1","unstructured":"T. B. Moyers T. Martin J. K. Manuel W. R. Miller and D. Ernst. 2010. Revised global scales: Motivational interviewing treatment integrity 3.1. 1 (MITI 3.1. 1). Unpublished manuscript University of New Mexico Albuquerque NM.  T. B. Moyers T. Martin J. K. Manuel W. R. Miller and D. Ernst. 2010. Revised global scales: Motivational interviewing treatment integrity 3.1. 1 (MITI 3.1. 1). Unpublished manuscript University of New Mexico Albuquerque NM."},{"key":"e_1_2_1_130_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12160-016-9830-8"},{"key":"e_1_2_1_131_1","doi-asserted-by":"publisher","DOI":"10.1162\/089976606775623289"},{"key":"e_1_2_1_132_1","doi-asserted-by":"publisher","DOI":"10.1093\/iwc\/iww034"},{"key":"e_1_2_1_133_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-015-3128-x"},{"key":"e_1_2_1_134_1","volume-title":"Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI\u201918)","author":"Nobles Alicia L.","unstructured":"Alicia L. Nobles , Jeffrey J. Glenn , Kamran Kowsari , Bethany A. Teachman , and Laura E. Barnes . 2018. Identification of imminent suicide risk among young adults using text messages . In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI\u201918) . ACM, Paper 413, 11 pages. DOI:https:\/\/doi.org\/10.1145\/3173574.3173987 10.1145\/3173574.3173987 Alicia L. Nobles, Jeffrey J. Glenn, Kamran Kowsari, Bethany A. Teachman, and Laura E. Barnes. 2018. Identification of imminent suicide risk among young adults using text messages. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI\u201918). ACM, Paper 413, 11 pages. DOI:https:\/\/doi.org\/10.1145\/3173574.3173987"},{"key":"e_1_2_1_135_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330738"},{"key":"e_1_2_1_136_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2016.08.174"},{"key":"e_1_2_1_137_1","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3173905"},{"key":"#cr-split#-e_1_2_1_138_1.1","doi-asserted-by":"crossref","unstructured":"Sharon Oviatt Bj\u00f6rn Schuller Philip R. Cohen Daniel Sonntag Gerasimos Potamianos and Antonio Kr\u00fcger (Eds.). 2018. The Handbook of Multimodal-Multisensor Interfaces. ACM and Morgan 8 Claypool xvii--xix. DOI:https:\/\/doi.org\/10.1145\/3107990.3107991 10.1145\/3107990.3107991","DOI":"10.1145\/3107990.3107991"},{"key":"#cr-split#-e_1_2_1_138_1.2","doi-asserted-by":"crossref","unstructured":"Sharon Oviatt Bj\u00f6rn Schuller Philip R. Cohen Daniel Sonntag Gerasimos Potamianos and Antonio Kr\u00fcger (Eds.). 2018. The Handbook of Multimodal-Multisensor Interfaces. ACM and Morgan 8 Claypool xvii--xix. DOI:https:\/\/doi.org\/10.1145\/3107990.3107991","DOI":"10.1145\/3107990.3107991"},{"key":"e_1_2_1_139_1","doi-asserted-by":"publisher","DOI":"10.5555\/1827616.1827621"},{"key":"e_1_2_1_140_1","doi-asserted-by":"publisher","DOI":"10.4108\/icst.pervasivehealth.2014.255070"},{"key":"e_1_2_1_141_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2017.09.001"},{"key":"e_1_2_1_142_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-03553-2"},{"key":"e_1_2_1_143_1","doi-asserted-by":"publisher","DOI":"10.1504\/IJKEDM.2015.074076"},{"key":"e_1_2_1_144_1","doi-asserted-by":"publisher","DOI":"10.1300\/J017v16n02_05"},{"key":"e_1_2_1_145_1","doi-asserted-by":"publisher","DOI":"10.5555\/1572306.1572327"},{"key":"e_1_2_1_146_1","doi-asserted-by":"publisher","DOI":"10.1109\/CBMS.2004.1311759"},{"key":"e_1_2_1_147_1","doi-asserted-by":"publisher","DOI":"10.5220\/0005237700250032"},{"key":"e_1_2_1_148_1","doi-asserted-by":"publisher","DOI":"10.1145\/1978942.1979047"},{"key":"e_1_2_1_149_1","volume-title":"Jennifer Wortman Vaughan, and Hanna Wallach","author":"Poursabzi-Sangdeh Forough","year":"2018","unstructured":"Forough Poursabzi-Sangdeh , Daniel G. Goldstein , Jake M. Hofman , Jennifer Wortman Vaughan, and Hanna Wallach . 2018 . Manipulating and measuring model interpretability. arXiv:1802.07810. DOI:https:\/\/arxiv.org\/abs\/1802.07810 Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, and Hanna Wallach. 2018. Manipulating and measuring model interpretability. arXiv:1802.07810. DOI:https:\/\/arxiv.org\/abs\/1802.07810"},{"key":"e_1_2_1_150_1","first-page":"1","article-title":"Moments of change: Analyzing peer-based cognitive support in online mental health forums. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI\u201919). ACM","volume":"64","author":"Pruksachatkun Yada","year":"2019","unstructured":"Yada Pruksachatkun , Sachin R. Pendse , and Amit Sharma . 2019 . Moments of change: Analyzing peer-based cognitive support in online mental health forums. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI\u201919). ACM , Paper 64 , 1 -- 13 . DOI:https:\/\/doi.org\/10.1145\/3290605.3300294 10.1145\/3290605.3300294 Yada Pruksachatkun, Sachin R. Pendse, and Amit Sharma. 2019. Moments of change: Analyzing peer-based cognitive support in online mental health forums. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI\u201919). ACM, Paper 64, 1--13. DOI:https:\/\/doi.org\/10.1145\/3290605.3300294","journal-title":"Paper"},{"key":"e_1_2_1_151_1","doi-asserted-by":"publisher","DOI":"10.1109\/IEMBS.2011.6090613"},{"key":"e_1_2_1_152_1","doi-asserted-by":"publisher","DOI":"10.1145\/3089341.3089347"},{"key":"e_1_2_1_153_1","doi-asserted-by":"publisher","DOI":"10.1145\/2030112.2030164"},{"key":"e_1_2_1_154_1","doi-asserted-by":"publisher","DOI":"10.1145\/3279963.3279968"},{"key":"e_1_2_1_155_1","doi-asserted-by":"publisher","DOI":"10.1145\/3347320.3357697"},{"key":"e_1_2_1_156_1","volume-title":"CBT. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI\u201916)","author":"Rennick-Egglestone Stefan","year":"2016","unstructured":"Stefan Rennick-Egglestone , Sarah Knowles , Gill Toms , Penny Bee , Karina Lovell , and Peter Bower . 2016 . Health technologies sin the wild\u2019: Experiences of engagement with computerised CBT. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI\u201916) . ACM, 2124--2135. DOI:https:\/\/doi.org\/10.1145\/2858036.2858128 10.1145\/2858036.2858128 Stefan Rennick-Egglestone, Sarah Knowles, Gill Toms, Penny Bee, Karina Lovell, and Peter Bower. 2016. Health technologies sin the wild\u2019: Experiences of engagement with computerised CBT. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI\u201916). ACM, 2124--2135. DOI:https:\/\/doi.org\/10.1145\/2858036.2858128"},{"key":"e_1_2_1_157_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.brat.2015.10.005"},{"key":"e_1_2_1_158_1","volume-title":"Lars Vedel Kessing, and Jakob E. Bardram","author":"Rohani Darius A.","year":"2018","unstructured":"Darius A. Rohani , Maria Faurholt-Jepsen , Lars Vedel Kessing, and Jakob E. Bardram . 2018 . Correlations between objective behavioral features collected from mobile and wearable devices and depressive mood symptoms in patients with affective disorders: Systematic review. JMIR mHealth and uHealth 6, 8 (2018), e165. DOI:https:\/\/doi.org\/10.2196\/mhealth.9691 10.2196\/mhealth.9691 Darius A. Rohani, Maria Faurholt-Jepsen, Lars Vedel Kessing, and Jakob E. Bardram. 2018. Correlations between objective behavioral features collected from mobile and wearable devices and depressive mood symptoms in patients with affective disorders: Systematic review. JMIR mHealth and uHealth 6, 8 (2018), e165. DOI:https:\/\/doi.org\/10.2196\/mhealth.9691"},{"key":"e_1_2_1_159_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-3959(83)90125-2"},{"key":"e_1_2_1_160_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553490"},{"key":"e_1_2_1_161_1","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-019-0048-x"},{"key":"e_1_2_1_162_1","doi-asserted-by":"publisher","DOI":"10.1037\/h0077714"},{"key":"e_1_2_1_163_1","doi-asserted-by":"publisher","DOI":"10.1207\/s15327752jpa6601_2"},{"key":"e_1_2_1_164_1","volume-title":"Kording","author":"Saeb Sohrab","year":"2016","unstructured":"Sohrab Saeb , Luca Lonini , Arun Jayaraman , David C. Mohr , and Konrad P . Kording . 2016 . Voodoo machine learning for clinical predictions. Biorxiv , 059774. DOI:https:\/\/doi.org\/10.1101\/059774 10.1101\/059774 Sohrab Saeb, Luca Lonini, Arun Jayaraman, David C. Mohr, and Konrad P. Kording. 2016. Voodoo machine learning for clinical predictions. Biorxiv, 059774. DOI:https:\/\/doi.org\/10.1101\/059774"},{"key":"e_1_2_1_165_1","doi-asserted-by":"publisher","DOI":"10.1145\/3134727"},{"key":"e_1_2_1_166_1","volume-title":"Proceedings of the International AAAI Conference on Web and Social Media 13","author":"Saha Koustuv","year":"2019","unstructured":"Koustuv Saha , Benjamin Sugar , John Torous , Bruno Abrahao , Emre K\u0131c\u0131man , and Munmun De Choudhury . 2019 . A social media study on the effects of psychiatric medication use . In Proceedings of the International AAAI Conference on Web and Social Media 13 , 1 (2019), 440--451. DOI:https:\/\/wvvw.aaai.org\/ojs\/index.php\/ICWSM\/article\/view\/3242 Koustuv Saha, Benjamin Sugar, John Torous, Bruno Abrahao, Emre K\u0131c\u0131man, and Munmun De Choudhury. 2019. A social media study on the effects of psychiatric medication use. In Proceedings of the International AAAI Conference on Web and Social Media 13, 1 (2019), 440--451. DOI:https:\/\/wvvw.aaai.org\/ojs\/index.php\/ICWSM\/article\/view\/3242"},{"key":"e_1_2_1_167_1","doi-asserted-by":"publisher","DOI":"10.1145\/3361108"},{"key":"e_1_2_1_168_1","volume-title":"Proceedings of the ACM on Interactive Mobile Wearable Ubiquitous Technology 2, 2, Article 81","author":"Salekin Asif","year":"2018","unstructured":"Asif Salekin , Jeremy W. Eberle , Jeffrey J. Glenn , Bethany A. Teachman , and John A. Stankovic . 2018. A weakly supervised learning framework for detecting social anxiety and depression . Proceedings of the ACM on Interactive Mobile Wearable Ubiquitous Technology 2, 2, Article 81 ( 2018 ), 26 pages. DOI:https:\/\/doi.org\/10.1145\/3214284 10.1145\/3214284 Asif Salekin, Jeremy W. Eberle, Jeffrey J. Glenn, Bethany A. Teachman, and John A. Stankovic. 2018. A weakly supervised learning framework for detecting social anxiety and depression. Proceedings of the ACM on Interactive Mobile Wearable Ubiquitous Technology 2, 2, Article 81 (2018), 26 pages. DOI:https:\/\/doi.org\/10.1145\/3214284"},{"key":"e_1_2_1_169_1","volume-title":"NSUDH Series H-53)","author":"SAMHS (Substance Abuse and Mental Health Services Administration","unstructured":"SAMHS (Substance Abuse and Mental Health Services Administration ). 2018. Key substance use and mental health indicators in the United States: Results from the 2017 National Survey on Drug Use and Health (HHS Publication No. SMA 18-5068 , NSUDH Series H-53) . Center for Behavioral Health Statistics and Quality , Substance Abuse and Mental Health Services Administration, Rockville, MD. Retrieved from https:\/\/www.samhsa.gov\/data\/sites\/default\/files\/cbhsq-reports\/NSDUHFFR2017\/NSDUHFFR2017.pdf. SAMHS (Substance Abuse and Mental Health Services Administration). 2018. Key substance use and mental health indicators in the United States: Results from the 2017 National Survey on Drug Use and Health (HHS Publication No. SMA 18-5068, NSUDH Series H-53). Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration, Rockville, MD. Retrieved from https:\/\/www.samhsa.gov\/data\/sites\/default\/files\/cbhsq-reports\/NSDUHFFR2017\/NSDUHFFR2017.pdf."},{"key":"e_1_2_1_170_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300475"},{"key":"e_1_2_1_171_1","volume-title":"Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI\u201918)","author":"Schroeder Jessica","unstructured":"Jessica Schroeder , Chelsey Wilkes , Kael Rowan , Arturo Toledo , Ann Paradiso , Mary Czerwinski , Gloria Mark , and Marsha M. Linehan . 2018. Pocket Skills: A conversational mobile web app to support dialectical behavioral therapy . In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI\u201918) . ACM, Paper 398, 15 pages. DOI:https:\/\/doi.org\/10.1145\/3173574.3173972 10.1145\/3173574.3173972 Jessica Schroeder, Chelsey Wilkes, Kael Rowan, Arturo Toledo, Ann Paradiso, Mary Czerwinski, Gloria Mark, and Marsha M. Linehan. 2018. Pocket Skills: A conversational mobile web app to support dialectical behavioral therapy. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI\u201918). ACM, Paper 398, 15 pages. DOI:https:\/\/doi.org\/10.1145\/3173574.3173972"},{"key":"e_1_2_1_172_1","doi-asserted-by":"publisher","DOI":"10.1002\/da.22649"},{"key":"e_1_2_1_173_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0033291719000151"},{"key":"e_1_2_1_174_1","volume-title":"Blaschko","author":"Sidahmed Hakim","year":"2016","unstructured":"Hakim Sidahmed , Elena Prokofyeva , and Matthew B . Blaschko . 2016 . Discovering predictors of mental health service utilization with k-support regularized logistic regression. Information Sciences 329, C ( 2016), 937--949. DOI:https:\/\/doi.org\/10.1016\/j.ins.2015.03.069 10.1016\/j.ins.2015.03.069 Hakim Sidahmed, Elena Prokofyeva, and Matthew B. Blaschko. 2016. Discovering predictors of mental health service utilization with k-support regularized logistic regression. Information Sciences 329, C (2016), 937--949. DOI:https:\/\/doi.org\/10.1016\/j.ins.2015.03.069"},{"key":"e_1_2_1_175_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-25044-6_29"},{"key":"e_1_2_1_176_1","doi-asserted-by":"publisher","DOI":"10.1145\/3329189.3329213"},{"key":"e_1_2_1_177_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330730"},{"key":"e_1_2_1_178_1","volume-title":"Proceedings of the 2015 International Conference on Advanced Research in Computer Science Engineering and Technology (ICARCSET\u201915)","author":"Sri Nandhini B.","unstructured":"B. Sri Nandhini and J. I. Sheeba . 2015. cyberbullying detection and classification using information retrieval algorithm . In Proceedings of the 2015 International Conference on Advanced Research in Computer Science Engineering and Technology (ICARCSET\u201915) . ACM, Paper 20, 5 pages. DOI:http:\/\/dx.doi.org\/10.1145\/2743065.2743085 10.1145\/2743065.2743085 B. Sri Nandhini and J. I. Sheeba. 2015. cyberbullying detection and classification using information retrieval algorithm. In Proceedings of the 2015 International Conference on Advanced Research in Computer Science Engineering and Technology (ICARCSET\u201915). ACM, Paper 20, 5 pages. DOI:http:\/\/dx.doi.org\/10.1145\/2743065.2743085"},{"key":"e_1_2_1_179_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-018-0934-5"},{"key":"e_1_2_1_180_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2008.06-07-550"},{"key":"e_1_2_1_181_1","volume-title":"Lionel Rigoux, et al.","author":"Stephan Klaas E.","year":"2017","unstructured":"Klaas E. Stephan , Florian Schlagenhauf , Quentin J. M. Huys , Sudhir Raman , Eduardo A. Aponte , Kay Henning Brodersen , Lionel Rigoux, et al. 2017 . Computational neuroimaging strategies for single patient predictions. Neuroimage 145, Pt. B ( 2017), 180--199. DOI:https:\/\/doi.org\/10.1016\/j.neuroimage.2016.06.038 10.1016\/j.neuroimage.2016.06.038 Klaas E. Stephan, Florian Schlagenhauf, Quentin J. M. Huys, Sudhir Raman, Eduardo A. Aponte, Kay Henning Brodersen, Lionel Rigoux, et al. 2017. Computational neuroimaging strategies for single patient predictions. Neuroimage 145, Pt. B (2017), 180--199. DOI:https:\/\/doi.org\/10.1016\/j.neuroimage.2016.06.038"},{"key":"e_1_2_1_182_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9280.2007.01987.x"},{"key":"e_1_2_1_183_1","doi-asserted-by":"publisher","DOI":"10.1006\/rtim.1998.0139"},{"key":"e_1_2_1_184_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340555.3356095"},{"key":"e_1_2_1_185_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2008.05-07-525"},{"key":"e_1_2_1_186_1","volume-title":"Machine Learning for Absolute Beginners. A Plain English Introduction","author":"Theobald Oliver","unstructured":"Oliver Theobald . 2017. Machine Learning for Absolute Beginners. A Plain English Introduction . Scatterplot Press . Oliver Theobald. 2017. Machine Learning for Absolute Beginners. A Plain English Introduction. Scatterplot Press."},{"key":"e_1_2_1_187_1","doi-asserted-by":"publisher","DOI":"10.1145\/2858036.2858182"},{"key":"e_1_2_1_188_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783446.2783586"},{"key":"e_1_2_1_189_1","doi-asserted-by":"publisher","DOI":"10.1145\/3381342"},{"key":"e_1_2_1_190_1","doi-asserted-by":"publisher","DOI":"10.1192\/bjp.bp.106.025791"},{"key":"e_1_2_1_191_1","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.6793"},{"key":"e_1_2_1_192_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2488196"},{"key":"e_1_2_1_193_1","doi-asserted-by":"publisher","DOI":"10.1145\/2769493.2769572"},{"key":"e_1_2_1_194_1","doi-asserted-by":"publisher","DOI":"10.14236\/ewic\/HCI2018.4"},{"key":"e_1_2_1_195_1","doi-asserted-by":"publisher","DOI":"10.1162\/089976603322297296"},{"key":"e_1_2_1_196_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988257.2988258"},{"key":"e_1_2_1_197_1","volume-title":"Proceedings of the 1st International Workshop on Mobile Development (Mobile! 2016","author":"Dominguez Veiga Jose Juan","year":"1854","unstructured":"Jose Juan Dominguez Veiga and Tomas E. Ward . 2016. Data collection requirements for mobile connected health: An end user development approach . In Proceedings of the 1st International Workshop on Mobile Development (Mobile! 2016 ). ACM, 23--30. DOI:https:\/\/doi.org\/10.1145\/300 1854 .3001856 10.1145\/3001854.3001856 Jose Juan Dominguez Veiga and Tomas E. Ward. 2016. Data collection requirements for mobile connected health: An end user development approach. In Proceedings of the 1st International Workshop on Mobile Development (Mobile! 2016). ACM, 23--30. DOI:https:\/\/doi.org\/10.1145\/3001854.3001856"},{"key":"e_1_2_1_198_1","doi-asserted-by":"publisher","DOI":"10.1145\/2029956.2029962"},{"key":"e_1_2_1_199_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2006.10.126"},{"key":"e_1_2_1_200_1","volume-title":"Proceedings of the Genetic and Evolutionary Computation Conference (GECCO\u201919)","author":"Vu Tuong Manh","year":"1840","unstructured":"Tuong Manh Vu , Charlotte Probst , Joshua M. Epstein , Alan Brennan , Mark Strong , and Robin C. Purshouse . 2019. Toward inverse generative social science using multi-objective genetic programming . In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO\u201919) . Manuel L\u00f3pez-Ib\u00e1\u00f1ez (Ed.), ACM, 1356--1363. DOI:https:\/\/doi.org\/10.1145\/3321707.332 1840 10.1145\/3321707.3321840 Tuong Manh Vu, Charlotte Probst, Joshua M. Epstein, Alan Brennan, Mark Strong, and Robin C. Purshouse. 2019. Toward inverse generative social science using multi-objective genetic programming. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO\u201919). Manuel L\u00f3pez-Ib\u00e1\u00f1ez (Ed.), ACM, 1356--1363. DOI:https:\/\/doi.org\/10.1145\/3321707.3321840"},{"key":"e_1_2_1_201_1","volume-title":"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp\u201914)","author":"Wang Rui","year":"2048","unstructured":"Rui Wang , Fanglin Chen , Zhenyu Chen , Tianxing Li , Gabriella Harari , Stefanie Tignor , Xia Zhou , Dror Ben-Zeev , and Andrew T. Campbell . 2014. StudentLife: Assessing mental health, academic performance and behavioral trends of college students using smartphones . In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp\u201914) . ACM, 3--14. DOI:https:\/\/doi.org\/10.1145\/263 2048 .2632054 10.1145\/2632048.2632054 Rui Wang, Fanglin Chen, Zhenyu Chen, Tianxing Li, Gabriella Harari, Stefanie Tignor, Xia Zhou, Dror Ben-Zeev, and Andrew T. Campbell. 2014. StudentLife: Assessing mental health, academic performance and behavioral trends of college students using smartphones. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp\u201914). ACM, 3--14. DOI:https:\/\/doi.org\/10.1145\/2632048.2632054"},{"key":"e_1_2_1_202_1","doi-asserted-by":"publisher","DOI":"10.1037\/0022-3514.54.6.1063"},{"key":"e_1_2_1_203_1","volume-title":"Proceedings of the Annual Convention of the International Society for Traumatic Stress Studies.","volume":"462","author":"Weathers Frank W.","unstructured":"Frank W. Weathers , Brett T. Litz , Debra S. Herman , Jennifer A. Huska , and Terence M. Keane . 1993. The PTSD checklist (PCL): Reliability, validity, and diagnostic utility . In Proceedings of the Annual Convention of the International Society for Traumatic Stress Studies. Vol. 462 . Frank W. Weathers, Brett T. Litz, Debra S. Herman, Jennifer A. Huska, and Terence M. Keane. 1993. The PTSD checklist (PCL): Reliability, validity, and diagnostic utility. In Proceedings of the Annual Convention of the International Society for Traumatic Stress Studies. Vol. 462."},{"key":"e_1_2_1_204_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(13)61611-6"},{"key":"e_1_2_1_205_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240925.3240932"},{"key":"e_1_2_1_206_1","doi-asserted-by":"publisher","DOI":"10.1038\/nn.4478"},{"key":"e_1_2_1_207_1","volume-title":"Fact sheets: Depression. Last retrieved 11th","author":"World Health Organization (WHO). 2018.","year":"2019","unstructured":"World Health Organization (WHO). 2018. Fact sheets: Depression. Last retrieved 11th June 2019 from http:\/\/www.who.int\/mediacentre\/factsheets\/fs369\/en\/. World Health Organization (WHO). 2018. Fact sheets: Depression. Last retrieved 11th June 2019 from http:\/\/www.who.int\/mediacentre\/factsheets\/fs369\/en\/."},{"key":"e_1_2_1_208_1","volume-title":"Ameneh Gholipour Shahraki, and Osmar R. Zaiane","author":"Yadollahi Ali","year":"2017","unstructured":"Ali Yadollahi , Ameneh Gholipour Shahraki, and Osmar R. Zaiane . 2017 . Current state of text sentiment analysis from opinion to emotion mining. ACM Computing Surveys 50, 2, Article 25 (2017), 33 pages. DOI:https:\/\/doi.org\/10.1145\/3057270 10.1145\/3057270 Ali Yadollahi, Ameneh Gholipour Shahraki, and Osmar R. Zaiane. 2017. Current state of text sentiment analysis from opinion to emotion mining. ACM Computing Surveys 50, 2, Article 25 (2017), 33 pages. DOI:https:\/\/doi.org\/10.1145\/3057270"},{"key":"e_1_2_1_209_1","volume-title":"Proceedings of the 3rd International Conference on Medical and Health Informatics 2019 (ICMHI\u201919)","author":"Yang Hui","unstructured":"Hui Yang and Peter A. Bath . 2019. Automatic prediction of depression in older age . In Proceedings of the 3rd International Conference on Medical and Health Informatics 2019 (ICMHI\u201919) . ACM, 36--44. DOI:https:\/\/doi.org\/10.1145\/3340037.3340042 10.1145\/3340037.3340042 Hui Yang and Peter A. Bath. 2019. Automatic prediction of depression in older age. In Proceedings of the 3rd International Conference on Medical and Health Informatics 2019 (ICMHI\u201919). ACM, 36--44. DOI:https:\/\/doi.org\/10.1145\/3340037.3340042"},{"key":"e_1_2_1_210_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300468"},{"key":"e_1_2_1_211_1","doi-asserted-by":"publisher","DOI":"10.1145\/3110025.3123028"},{"key":"e_1_2_1_212_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300509"},{"key":"e_1_2_1_213_1","doi-asserted-by":"publisher","DOI":"10.1192\/bjp.133.5.429"},{"key":"e_1_2_1_214_1","doi-asserted-by":"publisher","DOI":"10.1145\/3285996.3286012"},{"key":"e_1_2_1_215_1","doi-asserted-by":"publisher","DOI":"10.1145\/3239283.3239321"},{"key":"e_1_2_1_216_1","doi-asserted-by":"publisher","DOI":"10.2196\/mental.8971"},{"key":"e_1_2_1_217_1","doi-asserted-by":"publisher","DOI":"10.1145\/3307334.3328574"},{"key":"e_1_2_1_218_1","doi-asserted-by":"publisher","DOI":"10.1145\/3359139"},{"key":"e_1_2_1_219_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-25261-2_3"},{"key":"e_1_2_1_220_1","volume-title":"Inferring functional brain states using temporal evolution of regularized classifiers. Intelligent Neuroscience","author":"Zhdanov Andrey","year":"2007","unstructured":"Andrey Zhdanov , Talma Hendler , Leslie Ungerleider , and Nathan Intrator . 2007. Inferring functional brain states using temporal evolution of regularized classifiers. Intelligent Neuroscience 2007 , Article 52069. DOI:https:\/\/doi.org\/10.1155\/2007\/52609 10.1155\/2007 Andrey Zhdanov, Talma Hendler, Leslie Ungerleider, and Nathan Intrator. 2007. Inferring functional brain states using temporal evolution of regularized classifiers. Intelligent Neuroscience 2007, Article 52069. DOI:https:\/\/doi.org\/10.1155\/2007\/52609"},{"key":"e_1_2_1_221_1","first-page":"1","article-title":"Extrapolating expected accuracies for large multi-class problems","volume":"19","author":"Zheng Charles","year":"2018","unstructured":"Charles Zheng , Rakesh Achanta , and Yuval Benjamini . 2018 . Extrapolating expected accuracies for large multi-class problems . Journal of Machine Learning Research 19 , 1 (January 2018), 2609--2638. Charles Zheng, Rakesh Achanta, and Yuval Benjamini. 2018. Extrapolating expected accuracies for large multi-class problems. Journal of Machine Learning Research 19, 1 (January 2018), 2609--2638.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_2_1_222_1","volume-title":"Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI\u201915)","author":"Zhou Dawei","year":"2015","unstructured":"Dawei Zhou , Jiebo Luo , Vincent Silenzio , Yun Zhou , Jile Hu , Glenn Currier , and Henry Kautz . 2015 . Tackling mental health by integrating unobtrusive multimodal sensing . In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI\u201915) . AAAI Press, 1401--1408. DOI:https:\/\/www.aaai.org\/ocs\/index.php\/AAAI\/AAAI15\/paper\/view\/9546\/9334b. Dawei Zhou, Jiebo Luo, Vincent Silenzio, Yun Zhou, Jile Hu, Glenn Currier, and Henry Kautz. 2015. Tackling mental health by integrating unobtrusive multimodal sensing. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI\u201915). AAAI Press, 1401--1408. DOI:https:\/\/www.aaai.org\/ocs\/index.php\/AAAI\/AAAI15\/paper\/view\/9546\/9334b."}],"container-title":["ACM Transactions on Computer-Human Interaction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3398069","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3398069","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:38:53Z","timestamp":1750199933000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3398069"}},"subtitle":["A Systematic Review of the HCI Literature to Support the Development of Effective and Implementable ML Systems"],"short-title":[],"issued":{"date-parts":[[2020,8,17]]},"references-count":224,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2020,10,31]]}},"alternative-id":["10.1145\/3398069"],"URL":"https:\/\/doi.org\/10.1145\/3398069","relation":{},"ISSN":["1073-0516","1557-7325"],"issn-type":[{"value":"1073-0516","type":"print"},{"value":"1557-7325","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8,17]]},"assertion":[{"value":"2019-09-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-05-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-08-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}