{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T06:59:45Z","timestamp":1776754785992,"version":"3.51.2"},"publisher-location":"Cham","reference-count":38,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030244088","type":"print"},{"value":"9783030244095","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,8,2]],"date-time":"2019-08-02T00:00:00Z","timestamp":1564704000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-24409-5_1","type":"book-chapter","created":{"date-parts":[[2019,8,1]],"date-time":"2019-08-01T09:03:14Z","timestamp":1564650194000},"page":"1-7","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["From Precision Medicine to Precision Health: A Full Angle from Diagnosis to Treatment and Prevention"],"prefix":"10.1007","author":[{"given":"Arash","family":"Shaban-Nejad","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martin","family":"Michalowski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,8,2]]},"reference":[{"key":"1_CR1","doi-asserted-by":"crossref","unstructured":"Shaban-Nejad, A., Brownstein, J.S., Buckeridge, D.L.: Public Health Intelligence and the Internet. Lecture Notes in Social Networks Series, Springer\/Nature International Publishing, Berlin (2017). ISBN. 978\u20133-319-68602-8","DOI":"10.1007\/978-3-319-68604-2"},{"key":"1_CR2","unstructured":"The Precision Medicine Initiative: Accessed on 20 Feb 2019 https:\/\/obamawhitehouse.archives.gov\/precision-medicine"},{"issue":"3","key":"1_CR3","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1038\/nrd.2017.226","volume":"17","author":"SA Dugger","year":"2018","unstructured":"Dugger, S.A., Platt, A., Goldstein, D.B.: Drug development in the era of precision medicine. Nat Rev Drug Discov. 17(3), 183\u2013196 (2018)","journal-title":"Nat Rev Drug Discov."},{"issue":"18","key":"1_CR4","doi-asserted-by":"publisher","first-page":"1941","DOI":"10.1001\/jama.2016.3867","volume":"315","author":"David A. Chambers","year":"2016","unstructured":"Chambers D.A., Feero, W.G., Khoury, M.J.: Convergence of implementation science, precision medicine, and the learning health care system: A new model for biomedical research. JAMA. 10315(18), 1941\u20131942 (2016)","journal-title":"JAMA"},{"key":"1_CR5","doi-asserted-by":"crossref","unstructured":"Juengst, E.T., McGowan, M.L.: Why does the shift from \u201cPersonalized Medicine\u201d to \u201cPrecision Health\u201d and \u201cWellness Genomics\u201d Matter? AMA J. Ethics. 20(9), E881\u2013890","DOI":"10.1001\/amajethics.2018.881"},{"key":"1_CR6","doi-asserted-by":"publisher","unstructured":"Shin, E.K., Mahajan, R., Akbilgic, O., Shaban Nejad, A.: Sociomarkers and biomarkers: Predictive modeling in identifying pediatric asthma patients at risk of hospital revisits. npj Digit. Med. 1(50) (2018). https:\/\/doi.org\/10.1038\/s41746-018-0056-y","DOI":"10.1038\/s41746-018-0056-y"},{"key":"1_CR7","doi-asserted-by":"publisher","first-page":"46281","DOI":"10.1109\/ACCESS.2018.2866069","volume":"6","author":"EK Shin","year":"2018","unstructured":"Shin, E.K., Shaban-Nejad, A.: Urban decay and pediatric asthma prevalence in memphis, tennessee: urban data integration for efficient population health surveillance. IEEE Access 6, 46281\u201346289 (2018). https:\/\/doi.org\/10.1109\/ACCESS.2018.2866069","journal-title":"IEEE Access"},{"issue":"1","key":"1_CR8","doi-asserted-by":"publisher","first-page":"e186963","DOI":"10.1001\/jamanetworkopen.2018.6963","volume":"2","author":"EK Shin","year":"2019","unstructured":"Shin, E.K., LeWinn, K., Bush, N., Tylavsky, F.A., Davis, R.L., Shaban-Nejad, A.: Association of maternal social relationships with cognitive development in early childhood. JAMA Netw. Open. 2(1), e186963 (2019)","journal-title":"JAMA Netw. Open."},{"issue":"5","key":"1_CR9","doi-asserted-by":"publisher","first-page":"e13498","DOI":"10.2196\/13498","volume":"6","author":"JH Brenas","year":"2019","unstructured":"Brenas, J.H., Shin, E.K., Shaban-Nejad, A.: Adverse childhood experiences ontology for mental health surveillance, research, and evaluation: advanced knowledge representation and semantic web techniques. JMIR Ment. Health 6(5), e13498 (2019). https:\/\/doi.org\/10.2196\/13498","journal-title":"JMIR Ment. Health"},{"key":"1_CR10","doi-asserted-by":"crossref","unstructured":"Shaban-Nejad, A., Michalowski, M., Buckeridge, D.L.: Health intelligence: how artificial intelligence transforms population and personalized health. npj Digit. Med. 1(53) (2018)","DOI":"10.1038\/s41746-018-0058-9"},{"issue":"2","key":"1_CR11","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1016\/j.jbi.2013.01.002","volume":"46","author":"S Wilk","year":"2013","unstructured":"Wilk, S., Michalowski, W., Michalowski, M., Farion, K., Hing, M., Mohapatra, S.: Mitigation of adverse interactions in pairs of clinical practice guidelines using constraint logic programming. J. Biomed. Inform. 46(2), 341\u2013353 (2013)","journal-title":"J. Biomed. Inform."},{"key":"1_CR12","unstructured":"Michalowski, M., Wilk, S., Tan, X., Michalowski, W.: First-order logic theory for manipulating clinical practice guidelines applied to comorbid patients: a case study. In: AMIA 2014 Annual Symposium, pp. 892\u2013898. Washington (2014). (Distinguished Paper Award nominee)"},{"issue":"2","key":"1_CR13","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.jbi.2016.12.002","volume":"66","author":"S Wilk","year":"2017","unstructured":"Wilk, S., Michalowski, M., Michalowski, W., Rosu, D., Carrier, M., Kezadri-Hamiaz, M.: Comprehensive mitigation framework for concurrent application of multiple clinical practice guidelines. J. Biomed. Inform. 66(2), 52\u201371 (2017)","journal-title":"J. Biomed. Inform."},{"key":"1_CR14","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1007\/978-3-319-59758-4_4","volume-title":"Artificial Intelligence in Medicine","author":"Szymon Wilk","year":"2017","unstructured":"Wilk, S., Fux, A., Michalowski, M., Peleg, P., Soffer, P.: Using constraint logic programming for the verification of customized decision models for clinical guidelines. In: 16th Conference on Artificial Intelligence in Medicine (AIME\u201917), pp. 37\u201347. Vienna, Austria (2017)"},{"key":"1_CR15","unstructured":"Michalowski, M., Wilk, S., Rosu, D., Kezadri-Hamiaz, M., Michalowski, W., Carrier, M.: Expanding a first-order logic mitigation framework to handle multimorbid patient preferences. In: AMIA 2015 Annual Symposium, pp. 895\u2013903. San Francisco CA (2015)"},{"key":"1_CR16","unstructured":"Michalowski, M., Michalowski, W., O\u2019Sullivan, D., Wilk, S., Carrier, M.: AFGuide system to support personalized management of atrial fibrillation.In: 2017 Joint Workshop on Health Intelligence (W3PHIAI 2017), San Francisco CA (2017)"},{"issue":"11","key":"1_CR17","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/s10916-018-1077-4","volume":"42","author":"M Peleg","year":"2018","unstructured":"Peleg, M., Michalowski, W., Wilk, S., Parimbelli, E., Bonaccio, S., O\u2019Sullivan, D., Michalowski, M., Quaglini, S., Carrier, M.: Ideating mobile health behavioral support for compliance to therapy for patients with chronic disease: a case study of atrial fibrillation management. J. Med. Syst. 42(11), 234\u2013249 (2018)","journal-title":"J. Med. Syst."},{"issue":"1","key":"1_CR18","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1111\/nyas.13271","volume":"1387","author":"A Shaban-Nejad","year":"2017","unstructured":"Shaban-Nejad, A., Lavigne, M., Okhmatovskaia, A., Buckeridge, D.L.: PopHR: a knowledge-based platform to support integration, analysis, and visualization of population health data. Ann. N. Y. Acad. Sci. 1387(1), 44\u201353 (2017)","journal-title":"Ann. N. Y. Acad. Sci."},{"key":"1_CR19","doi-asserted-by":"publisher","first-page":"21605","DOI":"10.1109\/ACCESS.2017.2761232","volume":"5","author":"Jon Hael Brenas","year":"2017","unstructured":"Brenas, J.H., Al Manir, M.S., Baker, C.J.O., Shaban-Nejad, A.: A malaria analytics framework to support evolution and interoperability of global health surveillance systems. IEEE Access 5, 21605\u201321619 (2017)","journal-title":"IEEE Access"},{"key":"1_CR20","doi-asserted-by":"crossref","unstructured":"Gao, Q., Gonzalez H., Ahammad. P.: MCA-based rule mining enables interpretable inference in clinical psychiatry. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_3"},{"key":"1_CR21","doi-asserted-by":"crossref","unstructured":"Lu, X.H., Mamiya, H, Vybihal, J., Ma, Y., Buckeridge, D.L.: Guiding public health policy by using grocery transaction data to predict demand for unhealthy beverages. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_16"},{"key":"1_CR22","doi-asserted-by":"crossref","unstructured":"Sakishita, M., Kishimoto, T., Takinami, A., and Eguchi, Y., Kano, Y.: Large-scale dialog corpus towards automatic mental disease diagnosis. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_10"},{"key":"1_CR23","doi-asserted-by":"crossref","unstructured":"Vente, D., Arandjelovic, O., Baron, V.O., Dombay, E., Gillespie, S.H.: Using machine learning for automatic counting of lipid-rich tuberculosis cells in fluorescence microscopy images. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_6"},{"key":"1_CR24","doi-asserted-by":"crossref","unstructured":"Mendiola, V., Doss, A., Adams, W., Ramos, J., Bruns, M., Cherian, J., Kohli, P., Goldberg, D., Hammond, T.: Automatic exercise recognition with machine learning. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_4"},{"key":"1_CR25","doi-asserted-by":"crossref","unstructured":"Narui, H., Shu, R., Ermon, S., Gonzalez-Navarro, F.F.: Domain adaptation for human fall detection using WiFi channel state information. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_17"},{"key":"1_CR26","doi-asserted-by":"crossref","unstructured":"Hagad, J.L. Fukui, K., Numao, M.: Deep visual models for EEG of mindfulness meditation in a workplace setting. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_12"},{"key":"1_CR27","doi-asserted-by":"crossref","unstructured":"Yan, K., Lu, H.: Evaluating ensemble learning impact on gene selection for automated cancer diagnosis. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_18"},{"key":"1_CR28","doi-asserted-by":"crossref","unstructured":"Huang, K., Nogueira, R.: EpiRL: A reinforcement learning agent to facilitate epistasis detection. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_19"},{"key":"1_CR29","doi-asserted-by":"crossref","unstructured":"Bhatia, P., Celikkaya, B., Khalilia, M.: End-to-end joint entity extraction and negation detection for clinical text. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_13"},{"key":"1_CR30","doi-asserted-by":"crossref","unstructured":"Bhatia, P., Arumae, K.: Dynamic transfer learning for named entity recognition. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_7"},{"key":"1_CR31","doi-asserted-by":"crossref","unstructured":"Daughton, A.R., Paul, M.J.: Constructing accurate confidence intervals when aggregating social media data for public health monitoring. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_2"},{"key":"1_CR32","doi-asserted-by":"crossref","unstructured":"Jiang, K., Feng, S., Calix, R.A., Bernard, G.R.: Assessment of word embedding techniques for identification of personal experience tweets pertaining to medication uses. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_5"},{"key":"1_CR33","doi-asserted-by":"crossref","unstructured":"Zheng, J., Finzel, R., Pakhomov, S., Gini, M.: Spoken dialogue systems for medication management. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_11"},{"key":"1_CR34","doi-asserted-by":"crossref","unstructured":"Panigutti, C., Guidotti, R., Monreale, A., Pedreschi, D.: Explaining multi-label black-box classifiers for health applications. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_9"},{"key":"1_CR35","doi-asserted-by":"crossref","unstructured":"Sakishita, M., Ogawa, C., Tsuchiya, K.J., Iwabuchi, T., Kishimoto, T., Kano, Y.: Autism spectrum disorder\u2019s severity prediction model using utterance features for automatic diagnosis support. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_8"},{"key":"1_CR36","doi-asserted-by":"crossref","unstructured":"Tao, S., Guo, Y., Zhu, C., Yang, J., Chen, H., Zhang, Y.: Highly efficient follicular segmentation in thyroid cytopathological whole slide image. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_14"},{"key":"1_CR37","doi-asserted-by":"crossref","unstructured":"Saito, T., Onishi, M., Yoda, I., Kuroshima, S., Kawashima, M., Uchida, K., Oda, J., Mishima, S., Yukioka, T.: Analysis of team medical care using integrated information from the trajectories of and conversations among medical personnel. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_15"},{"key":"1_CR38","doi-asserted-by":"crossref","unstructured":"Feng, W. Yu, Z., Kang, M., Gong, H., Ahn, T.H.: Practical evaluation of different omics data integration methods. In: Shaban-Nejad, A., Michalowski, M. (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare. Studies in Computational Intelligence. Springer, Berlin (2019)","DOI":"10.1007\/978-3-030-24409-5_20"}],"container-title":["Studies in Computational Intelligence","Precision Health and Medicine"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-24409-5_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,12,4]],"date-time":"2019-12-04T21:49:00Z","timestamp":1575496140000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-24409-5_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,2]]},"ISBN":["9783030244088","9783030244095"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-24409-5_1","relation":{},"ISSN":["1860-949X","1860-9503"],"issn-type":[{"value":"1860-949X","type":"print"},{"value":"1860-9503","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,8,2]]},"assertion":[{"value":"2 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"W3PHAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Health Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Honolulu, HI","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 January 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 February 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wphai2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/w3phiai2019.w3phi.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}