{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T11:51:08Z","timestamp":1776426668727,"version":"3.51.2"},"reference-count":98,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2022,5,28]],"date-time":"2022-05-28T00:00:00Z","timestamp":1653696000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,5,28]],"date-time":"2022-05-28T00:00:00Z","timestamp":1653696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Inf Syst Front"],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1007\/s10796-022-10282-5","type":"journal-article","created":{"date-parts":[[2022,5,28]],"date-time":"2022-05-28T03:28:22Z","timestamp":1653708502000},"page":"1261-1276","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":140,"title":["An AI-based Decision Support System for Predicting Mental Health Disorders"],"prefix":"10.1007","volume":"25","author":[{"given":"Salih","family":"Tutun","sequence":"first","affiliation":[]},{"given":"Marina E.","family":"Johnson","sequence":"additional","affiliation":[]},{"given":"Abdulaziz","family":"Ahmed","sequence":"additional","affiliation":[]},{"given":"Abdullah","family":"Albizri","sequence":"additional","affiliation":[]},{"given":"Sedat","family":"Irgil","sequence":"additional","affiliation":[]},{"given":"Ilker","family":"Yesilkaya","sequence":"additional","affiliation":[]},{"given":"Esma Nur","family":"Ucar","sequence":"additional","affiliation":[]},{"given":"Tanalp","family":"Sengun","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0407-9217","authenticated-orcid":false,"given":"Antoine","family":"Harfouche","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,5,28]]},"reference":[{"issue":"1","key":"10282_CR1","doi-asserted-by":"publisher","first-page":"137","DOI":"10.22070\/CPAP.2020.2929","volume":"18","author":"F Akhavan Abiri","year":"2020","unstructured":"Akhavan Abiri, F., & Shairi, M. R. (2020a). Short Forms of Symptom Checklist (SCL): Investigation of validity & Reliability. Clinical Psychology and Personality, 18(1), 137\u2013162. https:\/\/doi.org\/10.22070\/CPAP.2020.2929","journal-title":"Clinical Psychology and Personality"},{"issue":"2","key":"10282_CR2","doi-asserted-by":"publisher","first-page":"169","DOI":"10.22070\/CPAP.2020.2916","volume":"17","author":"F Akhavan Abiri","year":"2020","unstructured":"Akhavan Abiri, F., & Shairi, M. R. (2020b). Validity and Reliability of Symptom Checklist-90-Revised (SCL-90-R) and Brief Symptom Inventory-53 (BSI-53). Clinical Psychology and Personality, 17(2), 169\u2013195. https:\/\/doi.org\/10.22070\/CPAP.2020.2916","journal-title":"Clinical Psychology and Personality"},{"key":"10282_CR3","doi-asserted-by":"publisher","first-page":"102387","DOI":"10.1016\/J.IJINFOMGT.2021.102387","volume":"60","author":"S Akter","year":"2021","unstructured":"Akter, S., McCarthy, G., Sajib, S., Michael, K., Dwivedi, Y. K., D\u2019Ambra, J., & Shen, K. N. (2021). Algorithmic bias in data-driven innovation in the age of AI. International Journal of Information Management, 60, 102387. https:\/\/doi.org\/10.1016\/J.IJINFOMGT.2021.102387","journal-title":"International Journal of Information Management"},{"key":"10282_CR4","doi-asserted-by":"publisher","unstructured":"Americans, N., Article, S., Haghir, H., Mokhber, N., Azarpazhooh, M. R., Haghighi, M. B. \u2026 Plan, Y. (2013). \u2026 World Health Organization. The ICD-10 Classification of Mental and Behavioural Disorders. IACAPAP E-Textbook of Child and Adolescent Mental Health, 55(1993), 135\u2013139. https:\/\/doi.org\/10.4103\/0019","DOI":"10.4103\/0019"},{"issue":"3","key":"10282_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2196\/26811","volume":"8","author":"L Balcombe","year":"2021","unstructured":"Balcombe, L., & De Leo, D. (2021). Digital Mental Health Challenges and the Horizon Ahead for Solutions XSL \u2022 FO RenderX. JMIR Ment Health, 8(3), 1. https:\/\/doi.org\/10.2196\/26811","journal-title":"JMIR Ment Health"},{"issue":"2","key":"10282_CR6","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1037\/1099-9809.9.2.185","volume":"9","author":"SL Barker-Collo","year":"2003","unstructured":"Barker-Collo, S. L. (2003). Culture and validity of the Symptom Checklist-90-Revised and Profile of Mood States in a New Zealand student sample. Cultural Diversity and Ethnic Minority Psychology, 9(2), 185\u2013196. https:\/\/doi.org\/10.1037\/1099-9809.9.2.185","journal-title":"Cultural Diversity and Ethnic Minority Psychology"},{"issue":"2","key":"10282_CR7","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1111\/1556-4029.12681","volume":"60","author":"W Bernet","year":"2015","unstructured":"Bernet, W., Baker, A. J. L., & Verrocchio, M. C. (2015). Symptom Checklist-90-Revised Scores in Adult Children Exposed to Alienating Behaviors: An Italian Sample. Journal of Forensic Sciences, 60(2), 357\u2013362. https:\/\/doi.org\/10.1111\/1556-4029.12681","journal-title":"Journal of Forensic Sciences"},{"key":"10282_CR8","doi-asserted-by":"publisher","unstructured":"Borgesius, F. J. Z. (2020). Strengthening legal protection against discrimination by algorithms and artificial intelligence. 24(10), 1572\u20131593. https:\/\/doi.org\/10.1080\/13642987.2020.1743976","DOI":"10.1080\/13642987.2020.1743976"},{"key":"10282_CR9","doi-asserted-by":"publisher","first-page":"101475","DOI":"10.1016\/J.TECHSOC.2020.101475","volume":"64","author":"A Buhmann","year":"2021","unstructured":"Buhmann, A., & Fieseler, C. (2021). Towards a deliberative framework for responsible innovation in artificial intelligence. Technology in Society, 64, 101475. https:\/\/doi.org\/10.1016\/J.TECHSOC.2020.101475","journal-title":"Technology in Society"},{"issue":"13","key":"10282_CR10","doi-asserted-by":"publisher","first-page":"11391","DOI":"10.1016\/j.eswa.2012.04.033","volume":"39","author":"C Casado-Lumbreras","year":"2012","unstructured":"Casado-Lumbreras, C., Rodr\u00edguez-Gonz\u00e1lez, A., \u00c1lvarez-Rodr\u00edguez, J. M., & Colomo-Palacios, R. (2012). PsyDis: Towards a diagnosis support system for psychological disorders. Expert Systems with Applications, 39(13), 11391\u201311403. https:\/\/doi.org\/10.1016\/j.eswa.2012.04.033","journal-title":"Expert Systems with Applications"},{"issue":"1","key":"10282_CR11","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1093\/SCHBUL\/SBZ105","volume":"46","author":"C Chandler","year":"2020","unstructured":"Chandler, C., Foltz, P. W., & Elvev\u00e5g, B. (2020). Using Machine Learning in Psychiatry: The Need to Establish a Framework That Nurtures Trustworthiness. Schizophrenia Bulletin, 46(1), 11\u201314. https:\/\/doi.org\/10.1093\/SCHBUL\/SBZ105","journal-title":"Schizophrenia Bulletin"},{"issue":"4","key":"10282_CR12","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1001\/jamapsychiatry.2017.0025","volume":"74","author":"AM Chekroud","year":"2017","unstructured":"Chekroud, A. M., Gueorguieva, R., Krumholz, H. M., Trivedi, M. H., Krystal, J. H., & McCarthy, G. (2017). Reevaluating the efficacy and predictability of antidepressant treatments: A symptom clustering approach. JAMA Psychiatry, 74(4), 370\u2013378. https:\/\/doi.org\/10.1001\/jamapsychiatry.2017.0025","journal-title":"JAMA Psychiatry"},{"issue":"8","key":"10282_CR13","doi-asserted-by":"publisher","first-page":"2737","DOI":"10.3390\/IJERPH17082737","volume":"17","author":"IH Chen","year":"2020","unstructured":"Chen, I. H., Lin, C. Y., Zheng, X., & Griffiths, M. D. (2020). Assessing Mental Health for China\u2019s Police: Psychometric Features of the Self-Rating Depression Scale and Symptom Checklist 90-Revised. International Journal of Environmental Research and Public Health 2020, 17(8), 2737. https:\/\/doi.org\/10.3390\/IJERPH17082737.17","journal-title":"International Journal of Environmental Research and Public Health 2020"},{"issue":"2","key":"10282_CR14","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1001\/AMAJETHICS.2019.167","volume":"21","author":"IY Chen","year":"2019","unstructured":"Chen, I. Y., Szolovits, P., & Ghassemi, M. (2019). Can AI help reduce disparities in general medical and mental health care? AMA Journal of Ethics, 21(2), 167\u2013179. https:\/\/doi.org\/10.1001\/AMAJETHICS.2019.167","journal-title":"AMA Journal of Ethics"},{"issue":"1","key":"10282_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-020-74710-9","volume":"10","author":"S Chen","year":"2020","unstructured":"Chen, S., Stromer, D., Alabdalrahim, H. A., Schwab, S., Weih, M., & Maier, A. (2020). Automatic dementia screening and scoring by applying deep learning on clock-drawing tests. Scientific Reports, 10(1), 1\u201311. https:\/\/doi.org\/10.1038\/s41598-020-74710-9","journal-title":"Scientific Reports"},{"issue":"7625","key":"10282_CR16","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1038\/538311a","volume":"538:7625","author":"K Crawford","year":"2016","unstructured":"Crawford, K., & Calo, R. (2016). There is a blind spot in AI research. Nature 2016, 538:7625(7625), 311\u2013313. https:\/\/doi.org\/10.1038\/538311a. 538","journal-title":"Nature 2016"},{"key":"10282_CR17","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1016\/J.COPSYC.2020.04.005","volume":"36","author":"S D\u2019Alfonso","year":"2020","unstructured":"D\u2019Alfonso, S. (2020). AI in mental health. Current Opinion in Psychology, 36, 112\u2013117. https:\/\/doi.org\/10.1016\/J.COPSYC.2020.04.005","journal-title":"Current Opinion in Psychology"},{"key":"10282_CR18","doi-asserted-by":"publisher","unstructured":"D\u2019Aquin, M., Troullinou, P., O, N. E., Cullen, A., Faller, G., & Holden, L. (2018). Towards an \u201cEthics by Design\u2019\u2019\u2019 Methodology for AI Research Projects.\u201d 18. https:\/\/doi.org\/10.1145\/3278721","DOI":"10.1145\/3278721"},{"issue":"6","key":"10282_CR19","doi-asserted-by":"publisher","first-page":"1541","DOI":"10.1108\/ITP-10-2021-871","volume":"34","author":"D Dennehy","year":"2021","unstructured":"Dennehy, D., Pappas, I. O., Wamba, S. F., & Michael, K. (2021). Socially responsible information systems development: the role of AI and business analytics. Information Technology and People, 34(6), 1541\u20131550. https:\/\/doi.org\/10.1108\/ITP-10-2021-871","journal-title":"Information Technology and People"},{"key":"10282_CR20","unstructured":"Derogatis, L. (2017). Symptom Checklist-90-Revised, Brief Symptom Inventory, and BSI-18. - PsycNET.Handbook of Psychological Assessment in Primary Care Settings,599\u2013629. https:\/\/psycnet.apa.org\/record\/2017-23747-023"},{"key":"10282_CR21","unstructured":"Derogatis, L., & Fitzpatrick, M. (2004). The SCL-90-R, the Brief Symptom Inventory (BSI), and the BSI-18. In The use of psychological testing for treatment planning and outcomes assessment: Instruments for adults (pp.\u00a01\u201341). https:\/\/psycnet.apa.org\/record\/2004-14941-001"},{"key":"10282_CR22","unstructured":"Derogatis, L., & Spencer, P. (1993). Brief Symptom Inventory"},{"key":"10282_CR23","doi-asserted-by":"publisher","unstructured":"Dignum, V., Baldoni, M., Baroglio, C., Caon, M., Chatila, R., Dennis, L. \u2026 De Wildt, T. (2018). Ethics by Design: Necessity or Curse? AIES 2018 - Proceedings of the 2018 AAAI\/ACM Conference on AI, Ethics, and Society, 18, 60\u201366. https:\/\/doi.org\/10.1145\/3278721.3278745","DOI":"10.1145\/3278721.3278745"},{"issue":"9","key":"10282_CR24","doi-asserted-by":"publisher","first-page":"706","DOI":"10.1093\/HEAPOL\/CZZ085","volume":"34","author":"S Docrat","year":"2019","unstructured":"Docrat, S., Besada, D., Cleary, S., Daviaud, E., & Lund, C. (2019). Mental health system costs, resources and constraints in South Africa: a national survey. Health Policy and Planning, 34(9), 706\u2013719. https:\/\/doi.org\/10.1093\/HEAPOL\/CZZ085","journal-title":"Health Policy and Planning"},{"key":"10282_CR25","doi-asserted-by":"publisher","first-page":"101889","DOI":"10.1016\/J.CPR.2020.101889","volume":"80","author":"F Fabiano","year":"2020","unstructured":"Fabiano, F., & Haslam, N. (2020). Diagnostic inflation in the DSM: A meta-analysis of changes in the stringency of psychiatric diagnosis from DSM-III to DSM-5. Clinical Psychology Review, 80, 101889. https:\/\/doi.org\/10.1016\/J.CPR.2020.101889","journal-title":"Clinical Psychology Review"},{"issue":"1","key":"10282_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/S12888-021-03190-6","volume":"21:1","author":"G Fellmeth","year":"2021","unstructured":"Fellmeth, G., Harrison, S., Opondo, C., Nair, M., Kurinczuk, J. J., & Alderdice, F. (2021). Validated screening tools to identify common mental disorders in perinatal and postpartum women in India: a systematic review and meta-analysis. BMC Psychiatry 2021, 21:1(1), 1\u201310. https:\/\/doi.org\/10.1186\/S12888-021-03190-6. 21","journal-title":"BMC Psychiatry 2021"},{"key":"10282_CR27","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1007\/978-3-030-81907-1_2","volume":"144","author":"L Floridi","year":"2021","unstructured":"Floridi, L., & Cowls, J. (2021). A Unified Framework of Five Principles for AI in Society. Philosophical Studies Series, 144, 5\u201317. https:\/\/doi.org\/10.1007\/978-3-030-81907-1_2","journal-title":"Philosophical Studies Series"},{"key":"10282_CR28","doi-asserted-by":"publisher","first-page":"120482","DOI":"10.1016\/J.TECHFORE.2020.120482","volume":"164","author":"S Fosso Wamba","year":"2021","unstructured":"Fosso Wamba, S., Bawack, R. E., Guthrie, C., Queiroz, M. M., & Carillo, K. D. A. (2021). Are we preparing for a good AI society? A bibliometric review and research agenda. Technological Forecasting and Social Change, 164, 120482. https:\/\/doi.org\/10.1016\/J.TECHFORE.2020.120482","journal-title":"Technological Forecasting and Social Change"},{"key":"10282_CR29","doi-asserted-by":"publisher","unstructured":"Fosso Wamba, S., & Queiroz, M. M. (2021). Responsible Artificial Intelligence as a Secret Ingredient for Digital Health: Bibliometric Analysis, Insights, and Research Directions. Information Systems Frontiers, 1\u201316. https:\/\/doi.org\/10.1007\/S10796-021-10142-8\/TABLES\/7","DOI":"10.1007\/S10796-021-10142-8\/TABLES\/7"},{"issue":"2","key":"10282_CR30","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1093\/poq\/nfp031","volume":"73","author":"M Galesic","year":"2009","unstructured":"Galesic, M., & Bosnjak, M. (2009). Effects of questionnaire length on participation and indicators of response quality in a web survey. Public Opinion Quarterly, 73(2), 349\u2013360. https:\/\/doi.org\/10.1093\/poq\/nfp031","journal-title":"Public Opinion Quarterly"},{"key":"10282_CR31","doi-asserted-by":"publisher","unstructured":"Gallardo-Pujol, D., & Pereda, N. (2013). Person-environment transactions: persionality traits moderate and mediate the effects. Personality and Mental Health, 7(April 2012), 102\u2013113. https:\/\/doi.org\/10.1002\/pmh","DOI":"10.1002\/pmh"},{"issue":"30","key":"10282_CR32","doi-asserted-by":"publisher","first-page":"3103","DOI":"10.1002\/sim.3906","volume":"29","author":"MJ Garcia-Zattera","year":"2010","unstructured":"Garcia-Zattera, M. J., Mutsvari, T., Jara, A., Declerck, D., & Lesaffre, E. (2010). Correcting for misclassification for a monotone disease process with an application in dental research. Statistics in Medicine, 29(30), 3103\u20133117. https:\/\/doi.org\/10.1002\/sim.3906","journal-title":"Statistics in Medicine"},{"key":"10282_CR34","doi-asserted-by":"publisher","unstructured":"Gerke, S., Minssen, T., & Cohen, G. (2020). Ethical and legal challenges of artificial intelligence-driven healthcare. Artificial Intelligence in Healthcare, 295\u2013336. https:\/\/doi.org\/10.1016\/B978-0-12-818438-7.00012-5","DOI":"10.1016\/B978-0-12-818438-7.00012-5"},{"issue":"11","key":"10282_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/S11920-019-1094-0","volume":"21:11","author":"S Graham","year":"2019","unstructured":"Graham, S., Depp, C., Lee, E. E., Nebeker, C., Tu, X., Kim, H. C., & Jeste, D. V. (2019). Artificial Intelligence for Mental Health and Mental Illnesses: an Overview. Current Psychiatry Reports 2019, 21:11(11), 1\u201318. https:\/\/doi.org\/10.1007\/S11920-019-1094-0. 21","journal-title":"Current Psychiatry Reports 2019"},{"key":"10282_CR37","doi-asserted-by":"publisher","unstructured":"Gupta, M., Parra, C. M., & Dennehy, D. (2021). Questioning Racial and Gender Bias in AI-based Recommendations: Do Espoused National Cultural Values Matter? Information Systems Frontiers, 1\u201317. https:\/\/doi.org\/10.1007\/S10796-021-10156-2\/TABLES\/5","DOI":"10.1007\/S10796-021-10156-2\/TABLES\/5"},{"issue":"3","key":"10282_CR38","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1002\/WPS.20572","volume":"17","author":"F Hanna","year":"2018","unstructured":"Hanna, F., Barbui, C., Dua, T., Lora, A., van Altena, M. R., & Saxena, S. (2018). Global mental health: how are we doing? World Psychiatry, 17(3), 368. https:\/\/doi.org\/10.1002\/WPS.20572","journal-title":"World Psychiatry"},{"key":"10282_CR39","doi-asserted-by":"publisher","unstructured":"Hao, B., Li, L., Li, A., & Zhu, T. (2013). Predicting mental health status on social media a preliminary study on microblog. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8024 LNCS(PART 2), 101\u2013110. https:\/\/doi.org\/10.1007\/978-3-642-39137-8-12","DOI":"10.1007\/978-3-642-39137-8-12"},{"issue":"2","key":"10282_CR40","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1053\/eujp.2001.0231","volume":"5","author":"J Hardt","year":"2001","unstructured":"Hardt, J., & Gerbershagen, H. U. (2001). Cross-validation of the SCL-27: A short psychometric screening instrument for chronic pain patients. European Journal of Pain, 5(2), 187\u2013197. https:\/\/doi.org\/10.1053\/eujp.2001.0231","journal-title":"European Journal of Pain"},{"key":"10282_CR41","first-page":"Doc08","volume":"5","author":"J Hardt","year":"2008","unstructured":"Hardt, J. (2008). The symptom checklist-27-plus (SCL-27-plus): a modern conceptualization of a traditional screening instrument. Psycho-Social Medicine, 5, Doc08","journal-title":"Psycho-Social Medicine"},{"key":"10282_CR42","doi-asserted-by":"publisher","unstructured":"Hastie, T., Tibshirani, R., & Friedman, J. (2009). Support Vector Machines and Flexible Discriminants. In The elements of statistical learning (pp.\u00a01\u201342). https:\/\/doi.org\/10.1007\/b94608_12","DOI":"10.1007\/b94608_12"},{"key":"10282_CR43","unstructured":"Hastie, T., Tibshirani, R., & Friedman, J. (2017). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed.). Springer Series in Statistics"},{"key":"10282_CR44","doi-asserted-by":"publisher","unstructured":"Hildenbrand, A. K., Nicholls, E. G., Aggarwal, R., Brody-Bizar, E., & Daly, B. P. (2015). Symptom Checklist-90-Revised (SCL-90-R). The Encyclopedia of Clinical Psychology, 1\u20135. https:\/\/doi.org\/10.1002\/9781118625392.wbecp495","DOI":"10.1002\/9781118625392.wbecp495"},{"key":"10282_CR45","unstructured":"Holi, M. (2003). Assessment of psychiatric symptoms using the SCL-90. [Matti Holi]"},{"key":"10282_CR46","unstructured":"IBM (2020). Trustworthy AI. https:\/\/www.ibm.com\/watson\/trustworthy-ai"},{"issue":"3","key":"10282_CR47","doi-asserted-by":"publisher","first-page":"674","DOI":"10.3390\/NU12030674","volume":"12","author":"C Imperatori","year":"2020","unstructured":"Imperatori, C., Bianciardi, E., Niolu, C., Fabbricatore, M., Gentileschi, P., Lorenzo, G. \u2026 Innamorati, M. (2020). The Symptom-Checklist-K-9 (SCL-K-9) Discriminates between Overweight\/Obese Patients with and without Significant Binge Eating Pathology: Psychometric Properties of an Italian Version. Nutrients 2020, 12(3), 674. https:\/\/doi.org\/10.3390\/NU12030674. 12","journal-title":"Nutrients 2020"},{"issue":"2","key":"10282_CR48","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1080\/21582041.2018.1563803","volume":"1563803","author":"R Iphofen","year":"2019","unstructured":"Iphofen, R., & Kritikos, M. (2019). Regulating artificial intelligence and robotics: ethics by design in a digital society. https:\/\/doi.org\/10.1080\/21582041.201816","journal-title":"Https:\/\/Doi.Org"},{"key":"10282_CR49","doi-asserted-by":"publisher","unstructured":"James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning (Vol. 103). Springer New York. https:\/\/doi.org\/10.1007\/978-1-4614-7138-7","DOI":"10.1007\/978-1-4614-7138-7"},{"issue":"2","key":"10282_CR50","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0009049","volume":"5","author":"R Jenkins","year":"2010","unstructured":"Jenkins, R., Kydd, R., Mullen, P., Thomson, K., Sculley, J., Kuper, S. \u2026 Wong, M. L. (2010). International migration of doctors, and its impact on availability of psychiatrists in low and middle income countries. PLoS ONE, 5(2), 1\u20139. https:\/\/doi.org\/10.1371\/journal.pone.0009049","journal-title":"PLoS ONE"},{"key":"10282_CR51","doi-asserted-by":"publisher","unstructured":"Johnson, M., Albizri, A., & Harfouche, A. (2021). Responsible Artificial Intelligence in Healthcare: Predicting and Preventing Insurance Claim Denials for Economic and Social Wellbeing. Information Systems Frontiers, 1\u201317. https:\/\/doi.org\/10.1007\/s10796-021-10137-5","DOI":"10.1007\/s10796-021-10137-5"},{"key":"10282_CR52","doi-asserted-by":"publisher","DOI":"10.1108\/IMDS-04-2021-0248\/FULL\/XML","author":"M Johnson","year":"2021","unstructured":"Johnson, M., Albizri, A., Harfouche, A., & Tutun, S. (2021). Digital transformation to mitigate emergency situations: increasing opioid overdose survival rates through explainable artificial intelligence. Industrial Management and Data Systems. https:\/\/doi.org\/10.1108\/IMDS-04-2021-0248\/FULL\/XML","journal-title":"Industrial Management and Data Systems"},{"key":"10282_CR53","doi-asserted-by":"publisher","unstructured":"Johnson, M., Albizri, A., & Simsek, S. (2020). Artificial intelligence in healthcare operations to enhance treatment outcomes: a framework to predict lung cancer prognosis. Annals of Operations Research, 1\u201331. https:\/\/doi.org\/10.1007\/s10479-020-03872-6","DOI":"10.1007\/s10479-020-03872-6"},{"key":"10282_CR54","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/J.PROCS.2021.05.020","volume":"185","author":"ME Khan","year":"2021","unstructured":"Khan, M. E., & Tutun, S. (2021). Understanding and Predicting Organ Donation Outcomes Using Network-based Predictive Analytics. Procedia Computer Science, 185, 185\u2013192. https:\/\/doi.org\/10.1016\/J.PROCS.2021.05.020","journal-title":"Procedia Computer Science"},{"issue":"1","key":"10282_CR55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/S12992-020-00621-Z","volume":"2020 16:1","author":"P Khanal","year":"2020","unstructured":"Khanal, P., Devkota, N., Dahal, M., Paudel, K., & Joshi, D. (2020). Mental health impacts among health workers during COVID-19 in a low resource setting: a cross-sectional survey from Nepal. Globalization and Health, 2020 16:1(1), 1\u201312. https:\/\/doi.org\/10.1186\/S12992-020-00621-Z. 16","journal-title":"Globalization and Health"},{"issue":"1","key":"10282_CR56","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1002\/WPS.20482","volume":"17","author":"AM Kilbourne","year":"2018","unstructured":"Kilbourne, A. M., Beck, K., Spaeth-Rublee, B., Ramanuj, P., O\u2019Brien, R. W., Tomoyasu, N., & Pincus, H. A. (2018). Measuring and improving the quality of mental health care: a global perspective. World Psychiatry, 17(1), 30\u201338. https:\/\/doi.org\/10.1002\/WPS.20482","journal-title":"World Psychiatry"},{"issue":"6","key":"10282_CR57","doi-asserted-by":"publisher","first-page":"376","DOI":"10.3961\/JPMPH.16.046","volume":"49","author":"JH Kim","year":"2016","unstructured":"Kim, J. H., & Jang, S. (2016). The Relationship Between Job Stress, Job Satisfaction, and the Symptom Checklist-90-Revision (SCL-90-R) in Marine Officers on Board. Journal of Preventive Medicine and Public Health, 49(6), 376. https:\/\/doi.org\/10.3961\/JPMPH.16.046","journal-title":"Journal of Preventive Medicine and Public Health"},{"issue":"13","key":"10282_CR58","doi-asserted-by":"publisher","first-page":"3521","DOI":"10.1073\/PNAS.1611835114\/-\/DCSUPPLEMENTAL","volume":"114","author":"J Kirkpatrick","year":"2017","unstructured":"Kirkpatrick, J., Pascanu, R., Rabinowitz, N., Veness, J., Desjardins, G., Rusu, A. A. \u2026 Hadsell, R. (2017). Overcoming catastrophic forgetting in neural networks. Proceedings of the National Academy of Sciences of the United States of America, 114(13), 3521\u20133526. https:\/\/doi.org\/10.1073\/PNAS.1611835114\/-\/DCSUPPLEMENTAL","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"},{"issue":"3","key":"10282_CR59","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1080\/15305058.2012.703734","volume":"13","author":"PM Kruyen","year":"2013","unstructured":"Kruyen, P. M., Emons, W. H. M., & Sijtsma, K. (2013). On the Shortcomings of Shortened Tests: A Literature Review. International Journal of Testing, 13(3), 223\u2013248. https:\/\/doi.org\/10.1080\/15305058.2012.703734","journal-title":"International Journal of Testing"},{"issue":"5","key":"10282_CR60","doi-asserted-by":"publisher","first-page":"10768","DOI":"10.1097\/MD.0000000000009783","volume":"97","author":"P Li","year":"2018","unstructured":"Li, P., Wang, F., Ji, G. Z., Miao, L., You, S., & Chen, X. (2018). The psychological results of 438 patients with persisting GERD symptoms by Symptom Checklist 90-Revised (SCL-90-R) questionnaire. Medicine (United States), 97(5), 10768. https:\/\/doi.org\/10.1097\/MD.0000000000009783","journal-title":"Medicine (United States)"},{"issue":"2","key":"10282_CR61","doi-asserted-by":"publisher","first-page":"1152","DOI":"10.1016\/j.dss.2005.10.007","volume":"42","author":"L Lin","year":"2006","unstructured":"Lin, L., Hu, P. J. H., & Liu Sheng, O. R. (2006). A decision support system for lower back pain diagnosis: Uncertainty management and clinical evaluations. Decision Support Systems, 42(2), 1152\u20131169. https:\/\/doi.org\/10.1016\/j.dss.2005.10.007","journal-title":"Decision Support Systems"},{"key":"10282_CR62","doi-asserted-by":"publisher","unstructured":"Lundqvist, L. O., & Schr\u00f6der, A. (2021). Evaluation of the SCL-9S, a short version of the symptom checklist-90-R, on psychiatric patients in Sweden by using Rasch analysis. https:\/\/doi.org\/10.1080\/08039488.2021.1901988","DOI":"10.1080\/08039488.2021.1901988"},{"key":"10282_CR63","doi-asserted-by":"publisher","unstructured":"Luxton, D. D. (2016). An Introduction to Artificial Intelligence in Behavioral and Mental Health Care. Artificial Intelligence in Behavioral and Mental Health Care, 1\u201326. https:\/\/doi.org\/10.1016\/B978-0-12-420248-1.00001-5","DOI":"10.1016\/B978-0-12-420248-1.00001-5"},{"key":"10282_CR64","doi-asserted-by":"publisher","unstructured":"Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), https:\/\/doi.org\/10.1177\/2053951716679679","DOI":"10.1177\/2053951716679679"},{"key":"10282_CR65","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1007\/978-3-319-33525-4_19","volume-title":"The Ethics of Biomedical Big Data","author":"BD Mittelstadt","year":"2016","unstructured":"Mittelstadt, B. D., & Floridi, L. (2016). The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts. The Ethics of Biomedical Big Data (1st ed., pp. 445\u2013480). Cham: Springer. https:\/\/doi.org\/10.1007\/978-3-319-33525-4_19","edition":"1"},{"key":"10282_CR66","doi-asserted-by":"publisher","DOI":"10.2139\/SSRN.3486518","author":"J Morley","year":"2019","unstructured":"Morley, J., Machado, C., Burr, C., Cowls, J., Taddeo, M., & Floridi, L. (2019). The Debate on the Ethics of AI in Health Care: A Reconstruction and Critical Review. SSRN Electronic Journal. https:\/\/doi.org\/10.2139\/SSRN.3486518","journal-title":"SSRN Electronic Journal"},{"issue":"1","key":"10282_CR67","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1753-4631-5-5","volume":"5","author":"A Mueller","year":"2011","unstructured":"Mueller, A., Candrian, G., Grane, V. A., Kropotov, J. D., Ponomarev, V. A., & Baschera, G. M. (2011). Discriminating between ADHD adults and controls using independent ERP components and a support vector machine: A validation study. Nonlinear Biomedical Physics, 5(1), 1\u201318. https:\/\/doi.org\/10.1186\/1753-4631-5-5","journal-title":"Nonlinear Biomedical Physics"},{"key":"10282_CR68","doi-asserted-by":"publisher","unstructured":"Nie, D., Ning, Y., & Zhu, T. (2012). Predicting mental health status in the context of web browsing. Proceedings of the 2012 IEEE\/WIC\/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT 2012, 185\u2013189. https:\/\/doi.org\/10.1109\/WI-IAT.2012.196","DOI":"10.1109\/WI-IAT.2012.196"},{"issue":"2","key":"10282_CR69","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/S00702-017-1828-2","volume":"2017 125:2","author":"K Ogasawara","year":"2017","unstructured":"Ogasawara, K., Nakamura, Y., Kimura, H., Aleksic, B., & Ozaki, N. (2017). Issues on the diagnosis and etiopathogenesis of mood disorders: reconsidering DSM-5. Journal of Neural Transmission, 2017 125:2(2), 211\u2013222. https:\/\/doi.org\/10.1007\/S00702-017-1828-2. 125","journal-title":"Journal of Neural Transmission"},{"issue":"2","key":"10282_CR70","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1046\/j.0001-690X.2003.00231.x","volume":"109","author":"LR Olsen","year":"2004","unstructured":"Olsen, L. R., Mortensen, E. L., & Bech, P. (2004). Prevalence of major depression and stress indicators in the Danish general population. Acta Psychiatrica Scandinavica, 109(2), 96\u2013103. https:\/\/doi.org\/10.1046\/j.0001-690X.2003.00231.x","journal-title":"Acta Psychiatrica Scandinavica"},{"key":"10282_CR71","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1007\/978-981-32-9705-0_12","volume":"1191","author":"SC Park","year":"2020","unstructured":"Park, S. C., & Kim, Y. K. (2020). Anxiety Disorders in the DSM-5: Changes, Controversies, and Future Directions. Advances in Experimental Medicine and Biology, 1191, 187\u2013196. https:\/\/doi.org\/10.1007\/978-981-32-9705-0_12","journal-title":"Advances in Experimental Medicine and Biology"},{"key":"10282_CR72","doi-asserted-by":"publisher","first-page":"102271","DOI":"10.1016\/J.IJINFOMGT.2020.102271","volume":"57","author":"CM Parra","year":"2021","unstructured":"Parra, C. M., Gupta, M., & Mikalef, P. (2021). Information and communication technologies (ICT)-enabled severe moral communities and how the (Covid19) pandemic might bring new ones. International Journal of Information Management, 57, 102271. https:\/\/doi.org\/10.1016\/J.IJINFOMGT.2020.102271","journal-title":"International Journal of Information Management"},{"key":"10282_CR73","doi-asserted-by":"publisher","unstructured":"Pechenizkiy, M., Tsymbal, A., Puuronen, S., & Pechenizkiy, O. (2006). Class noise and supervised learning in medical domains: The effect of feature extraction. Proceedings - IEEE Symposium on Computer-Based Medical Systems, 2006, 708\u2013713. https:\/\/doi.org\/10.1109\/CBMS.2006.65","DOI":"10.1109\/CBMS.2006.65"},{"issue":"9","key":"10282_CR74","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1016\/S2215-0366(18)30095-6","volume":"5","author":"A Perkins","year":"2018","unstructured":"Perkins, A., Ridler, J., Browes, D., Peryer, G., Notley, C., & Hackmann, C. (2018). Experiencing mental health diagnosis: a systematic review of service user, clinician, and carer perspectives across clinical settings. The Lancet Psychiatry, 5(9), 747\u2013764. https:\/\/doi.org\/10.1016\/S2215-0366(18)30095-6","journal-title":"The Lancet Psychiatry"},{"issue":"1","key":"10282_CR75","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/S12888-019-2081-Z","volume":"19:1","author":"I Petersen","year":"2019","unstructured":"Petersen, I., Bhana, A., Fairall, L. R., Selohilwe, O., Kathree, T., Baron, E. C. \u2026 Lund, C. (2019). Evaluation of a collaborative care model for integrated primary care of common mental disorders comorbid with chronic conditions in South Africa. BMC Psychiatry 2019, 19:1(1), 1\u201311. https:\/\/doi.org\/10.1186\/S12888-019-2081-Z. 19","journal-title":"BMC Psychiatry 2019"},{"key":"10282_CR76","unstructured":"Price, W. N. I. (2019). Medical AI and Contextual Bias. Harvard Journal of Law & Technology (Harvard JOLT), 33. https:\/\/heinonline.org\/HOL\/Page?handle=hein.journals\/hjlt33&id=71&div=&collection="},{"key":"10282_CR77","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-244X-13-104","volume":"13","author":"U Prinz","year":"2013","unstructured":"Prinz, U., Nutzinger, D. O., Schulz, H., Petermann, F., Braukhaus, C., & Andreas, S. (2013). Comparative psychometric analyses of the SCL-90-R and its short versions in patients with affective disorders. BMC Psychiatry, 13, 1\u20139. https:\/\/doi.org\/10.1186\/1471-244X-13-104","journal-title":"BMC Psychiatry"},{"key":"10282_CR78","doi-asserted-by":"publisher","unstructured":"Ransing, R., Ramalho, R., Orsolini, L., Adiukwu, F., Gonzalez-Diaz, J. M., Larnaout, A. \u2026 Kilic, O. (2020). Can COVID-19 related mental health issues be measured? Brain, Behavior, and Immunity, 88, 32. https:\/\/doi.org\/10.1016\/J.BBI.2020.05.049","DOI":"10.1016\/J.BBI.2020.05.049"},{"issue":"1","key":"10282_CR79","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1590\/S0100-879X2006000100014","volume":"39","author":"D Razzouk","year":"2006","unstructured":"Razzouk, D., Mari, J. J., Shirakawa, I., Wainer, J., & Sigulem, D. (2006). Decision support system for the diagnosis of schizophrenia disorders. Brazilian Journal of Medical and Biological Research, 39(1), 119\u2013128","journal-title":"Brazilian Journal of Medical and Biological Research"},{"key":"10282_CR80","doi-asserted-by":"publisher","unstructured":"Ritchie, H. (2018). Global burden of disease studies: Implications for mental and substance use disorders. In Health Affairs. Issue 6). Project HOPE, 35, https:\/\/doi.org\/10.1377\/HLTHAFF.2016.0082","DOI":"10.1377\/HLTHAFF.2016.0082"},{"issue":"12","key":"10282_CR81","doi-asserted-by":"publisher","first-page":"2057","DOI":"10.1007\/s10439-018-2104-9","volume":"46","author":"E Rovini","year":"2018","unstructured":"Rovini, E., Maremmani, C., Moschetti, A., Esposito, D., & Cavallo, F. (2018). Comparative Motor Pre-clinical Assessment in Parkinson\u2019s Disease Using Supervised Machine Learning Approaches. Annals of Biomedical Engineering, 46(12), 2057\u20132068. https:\/\/doi.org\/10.1007\/s10439-018-2104-9","journal-title":"Annals of Biomedical Engineering"},{"key":"10282_CR82","doi-asserted-by":"publisher","unstructured":"Rytil\u00e4-Manninen, M., Fr\u00f6jd, S., Haravuori, H., Lindberg, N., Marttunen, M., Kettunen, K., & Therman, S. (2016). Psychometric properties of the Symptom Checklist-90 in adolescent psychiatric inpatients and age- and gender-matched community youth. Child and Adolescent Psychiatry and Mental Health 2016 10:1, 10(1), 1\u201312. https:\/\/doi.org\/10.1186\/S13034-016-0111-X","DOI":"10.1186\/S13034-016-0111-X"},{"issue":"2","key":"10282_CR83","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1023\/A:1008931926181","volume":"9","author":"N Schmitz","year":"2000","unstructured":"Schmitz, N., Hartkamp, N., Kiuse, J., Franke, G. H., Reister, G., & Tress, W. (2000). The Symptom Check-List-90-R (SCL-90-R): A German validation study. Quality of Life Research, 9(2), 185\u2013193. https:\/\/doi.org\/10.1023\/A:1008931926181","journal-title":"Quality of Life Research"},{"issue":"2","key":"10282_CR84","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1093\/IJLIT\/EAZ004","volume":"27","author":"D Sch\u00f6nberger","year":"2019","unstructured":"Sch\u00f6nberger, D. (2019). Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications. International Journal of Law and Information Technology, 27(2), 171\u2013203. https:\/\/doi.org\/10.1093\/IJLIT\/EAZ004","journal-title":"International Journal of Law and Information Technology"},{"key":"10282_CR85","doi-asserted-by":"publisher","unstructured":"Sereda, Y., & Dembitskyi, S. (2016). Validity assessment of the symptom checklist SCL-90-R and shortened versions for the general population in Ukraine. BMC Psychiatry 2016 16:1, 16(1), 1\u201311. https:\/\/doi.org\/10.1186\/S12888-016-1014-3","DOI":"10.1186\/S12888-016-1014-3"},{"key":"10282_CR86","doi-asserted-by":"publisher","DOI":"10.1108\/JEIM-12-2019-0375","author":"S Simsek","year":"2020","unstructured":"Simsek, S., Albizri, A., Johnson, M., Custis, T., & Weikert, S. (2020). Predictive data analytics for contract renewals: a decision support tool for managerial decision-making. Journal of Enterprise Information Management. https:\/\/doi.org\/10.1108\/JEIM-12-2019-0375","journal-title":"Journal of Enterprise Information Management"},{"issue":"3","key":"10282_CR87","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1177\/070674371005500303","volume":"55","author":"M Sinyor","year":"2010","unstructured":"Sinyor, M., Schaffer, A., & Levitt, A. (2010). The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial: A review. Canadian Journal of Psychiatry, 55(3), 126\u2013135. https:\/\/doi.org\/10.1177\/070674371005500303","journal-title":"Canadian Journal of Psychiatry"},{"issue":"1","key":"10282_CR88","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1097\/YCO.0000000000000657","volume":"34","author":"C Sleep","year":"2021","unstructured":"Sleep, C., Lynam, D. R., & Miller, J. D. (2021). Personality impairment in the DSM-5 and ICD-11: Current standing and limitations. Current Opinion in Psychiatry, 34(1), 39\u201343. https:\/\/doi.org\/10.1097\/YCO.0000000000000657","journal-title":"Current Opinion in Psychiatry"},{"issue":"6","key":"10282_CR89","doi-asserted-by":"publisher","first-page":"913","DOI":"10.1007\/S10578-020-00968-9","volume":"51","author":"SL Stewart","year":"2020","unstructured":"Stewart, S. L., Celebre, A., Hirdes, J. P., & Poss, J. W. (2020). Risk of Suicide and Self-harm in Kids: The Development of an Algorithm to Identify High-Risk Individuals Within the Children\u2019s Mental Health System. Child Psychiatry and Human Development, 51(6), 913. https:\/\/doi.org\/10.1007\/S10578-020-00968-9","journal-title":"Child Psychiatry and Human Development"},{"issue":"5","key":"10282_CR90","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1145\/3398069","volume":"27","author":"B Thieme Anja","year":"2020","unstructured":"Thieme Anja, B., & Doherty Gavin. (2020). Machine Learning in Mental Health. ACM Transactions on Computer-Human Interaction (TOCHI), 27(5), 34. https:\/\/doi.org\/10.1145\/3398069","journal-title":"ACM Transactions on Computer-Human Interaction (TOCHI)"},{"issue":"8","key":"10282_CR91","doi-asserted-by":"publisher","first-page":"879","DOI":"10.1176\/appi.ps.55.8.879","volume":"55","author":"MH Trivedi","year":"2004","unstructured":"Trivedi, M. H., Kern, J. K., Grannemann, B. D., Altshuler, K. Z., & Sunderajan, P. (2004). A computerized clinical decision support system as a means of implementing depression guidelines. Psychiatric Services, 55(8), 879\u2013885. https:\/\/doi.org\/10.1176\/appi.ps.55.8.879","journal-title":"Psychiatric Services"},{"key":"10282_CR92","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/S00146-021-01154-8","volume":"1","author":"A Tsamados","year":"2021","unstructured":"Tsamados, A., Aggarwal, N., Cowls, J., Morley, J., Roberts, H., Taddeo, M., & Floridi, L. (2021). The ethics of algorithms: key problems and solutions. AI & SOCIETY 2021, 1, 1\u201316. https:\/\/doi.org\/10.1007\/S00146-021-01154-8","journal-title":"AI & SOCIETY 2021"},{"key":"10282_CR93","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1016\/J.ESWA.2017.02.029","volume":"78","author":"S Tutun","year":"2017","unstructured":"Tutun, S., Khasawneh, M. T., & Zhuang, J. (2017). New framework that uses patterns and relations to understand terrorist behaviors. Expert Systems with Applications, 78, 358\u2013375. https:\/\/doi.org\/10.1016\/J.ESWA.2017.02.029","journal-title":"Expert Systems with Applications"},{"key":"10282_CR94","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/2573234X.2022.2046514","volume":"2046514","author":"S Tutun","year":"2022","unstructured":"Tutun, S., Tosyali, A., Sangrody, H., Khasawneh, M., Johnson, M., Albizri, A., & Harfouche, A. (2022). Artificial intelligence in energy industry: forecasting electricity consumption through cohort intelligence & adaptive neural fuzzy inference system. Https:\/\/Doi.Org, 2046514, 1\u201318. https:\/\/doi.org\/10.1080\/2573234X.2022.2046514","journal-title":"Https:\/\/Doi.Org"},{"key":"10282_CR95","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1016\/J.PSYCHRES.2016.03.039","volume":"239","author":"R Urb\u00e1n","year":"2016","unstructured":"Urb\u00e1n, R., Arrindell, W. A., Demetrovics, Z., Unoka, Z., & Timman, R. (2016). Cross-cultural confirmation of bi-factor models of a symptom distress measure: Symptom Checklist-90-Revised in clinical samples. Psychiatry Research, 239, 265\u2013274. https:\/\/doi.org\/10.1016\/J.PSYCHRES.2016.03.039","journal-title":"Psychiatry Research"},{"issue":"5","key":"10282_CR96","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1007\/S11920-017-0780-Z","volume":"19","author":"ML Wainberg","year":"2017","unstructured":"Wainberg, M. L., Scorza, P., Shultz, J. M., Helpman, L., Mootz, J. J., Johnson, K. A. \u2026 Arbuckle, M. R. (2017). Challenges and Opportunities in Global Mental Health: a Research-to-Practice Perspective. Current Psychiatry Reports, 19(5), 28. https:\/\/doi.org\/10.1007\/S11920-017-0780-Z","journal-title":"Current Psychiatry Reports"},{"issue":"4","key":"10282_CR97","doi-asserted-by":"publisher","first-page":"3336","DOI":"10.1016\/j.eswa.2010.08.118","volume":"38","author":"WM Wang","year":"2011","unstructured":"Wang, W. M., & Cheung, C. F. (2011). A narrative-based reasoning with applications in decision support for social service organizations. Expert Systems with Applications, 38(4), 3336\u20133345. https:\/\/doi.org\/10.1016\/j.eswa.2010.08.118","journal-title":"Expert Systems with Applications"},{"key":"10282_CR98","unstructured":"WHO (2018). Mental health: strengthening our response. https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/mental-health-strengthening-our-response"},{"key":"10282_CR99","unstructured":"WHO (2020). World Mental Health Day: an opportunity to kick-start a massive scale-up in investment in mental health. https:\/\/www.who.int\/news\/item\/27-08-2020-world-mental-health-day-an-opportunity-to-kick-start-a-massive-scale-up-in-investment-in-mental-health"},{"key":"10282_CR100","doi-asserted-by":"publisher","unstructured":"Zhang, Z., Lin, W., Liu, M., & Mahmoud, M. (2020). Multimodal Deep Learning Framework for Mental Disorder Recognition. Proceedings \u2013 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2020, 344\u2013350. https:\/\/doi.org\/10.1109\/FG47880.2020.00033","DOI":"10.1109\/FG47880.2020.00033"}],"container-title":["Information Systems Frontiers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10796-022-10282-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10796-022-10282-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10796-022-10282-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T11:50:17Z","timestamp":1744199417000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10796-022-10282-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,28]]},"references-count":98,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["10282"],"URL":"https:\/\/doi.org\/10.1007\/s10796-022-10282-5","relation":{},"ISSN":["1387-3326","1572-9419"],"issn-type":[{"value":"1387-3326","type":"print"},{"value":"1572-9419","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,28]]},"assertion":[{"value":"21 April 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 May 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that there are no conflicts of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}]}}