{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T18:18:33Z","timestamp":1790533113380,"version":"4.1.0"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2016,10,18]],"date-time":"2016-10-18T00:00:00Z","timestamp":1476748800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2016,10,18]],"date-time":"2016-10-18T00:00:00Z","timestamp":1476748800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Transl Psychiatry"],"DOI":"10.1038\/tp.2015.182","type":"journal-article","created":{"date-parts":[[2016,10,18]],"date-time":"2016-10-18T09:47:52Z","timestamp":1476784072000},"page":"e921-e921","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":164,"title":["Predicting early psychiatric readmission with natural language processing of narrative discharge summaries"],"prefix":"10.1038","volume":"6","author":[{"given":"A","family":"Rumshisky","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M","family":"Ghassemi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"T","family":"Naumann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"P","family":"Szolovits","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"V M","family":"Castro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"T H","family":"McCoy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R H","family":"Perlis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2016,10,18]]},"reference":[{"key":"BFtp2015182_CR1","unstructured":"Anonymous. CMS Readmissions Reduction Program 2014. Available at http:\/\/www.cms.gov\/Medicare\/Medicare-Fee-for-Service-Payment\/AcuteInpatientPPS\/Readmissions-Reduction-Program.html; accessed on 30 March 2015."},{"key":"BFtp2015182_CR2","unstructured":"National Research Council (US) Committee on A Framework for Developing a New Taxonomy of Disease. Toward precision medicine: building a knowledge network for biomedical research and a new taxonomy of disease. National Academic Press: Washington DC, USA, 2011."},{"key":"BFtp2015182_CR3","doi-asserted-by":"publisher","first-page":"b3677","DOI":"10.1136\/bmj.b3677","volume":"339","author":"BY Reis","year":"2009","unstructured":"Reis BY, Kohane IS, Mandl KD . Longitudinal histories as predictors of future diagnoses of domestic abuse: modelling study. BMJ 2009; 339: b3677.","journal-title":"BMJ"},{"key":"BFtp2015182_CR4","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1016\/j.biopsych.2012.12.007","volume":"74","author":"RH Perlis","year":"2013","unstructured":"Perlis RH . A clinical risk stratification tool for predicting treatment resistance in major depressive disorder. Biol Psychiatry 2013; 74: 7\u201314.","journal-title":"Biol Psychiatry"},{"key":"BFtp2015182_CR5","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1017\/S0033291711000997","volume":"42","author":"R Perlis","year":"2012","unstructured":"Perlis R, Iosifescu D, Castro V, Murphy S, Gainer V, Minnier J et al. Using electronic medical records to enable large-scale studies in psychiatry: treatment resistant depression as a model. Psychol Med 2012; 42: 41\u201350.","journal-title":"Psychol Med"},{"key":"BFtp2015182_CR6","first-page":"281","volume":"13","author":"S Pakhomov","year":"2007","unstructured":"Pakhomov S, Weston SA, Jacobsen SJ, Chute CG, Meverden R, Roger VL et al. Electronic medical records for clinical research: application to the identification of heart failure. Am J Manag Care 2007; 13: 281\u2013288.","journal-title":"Am J Manag Care"},{"key":"BFtp2015182_CR7","doi-asserted-by":"publisher","first-page":"1120","DOI":"10.1002\/acr.20184","volume":"62","author":"KP Liao","year":"2010","unstructured":"Liao KP, Cai T, Gainer V, Goryachev S, Zeng-treitler Q, Raychaudhuri S et al. Electronic medical records for discovery research in rheumatoid arthritis. Arthritis Care Res 2010; 62: 1120\u20131127.","journal-title":"Arthritis Care Res"},{"key":"BFtp2015182_CR8","doi-asserted-by":"publisher","first-page":"i144","DOI":"10.1136\/amiajnl-2011-000351","volume":"18","author":"S Sohn","year":"2011","unstructured":"Sohn S, Kocher JPA, Chute CG, Savova GK . Drug side effect extraction from clinical narratives of psychiatry and psychology patients. J Am Med Inform Assoc 2011; 18: i144\u2013i149.","journal-title":"J Am Med Inform Assoc"},{"key":"BFtp2015182_CR9","first-page":"1244","volume":"2012","author":"K Haerian","year":"2012","unstructured":"Haerian K, Salmasian H, Friedman C . Methods for identifying suicide or suicidal ideation in EHRs. AMIA Annu Symp Proc 2012; 2012: 1244\u20131253.","journal-title":"AMIA Annu Symp Proc"},{"key":"BFtp2015182_CR10","first-page":"172","volume":"6","author":"PL Elkin","year":"2008","unstructured":"Elkin PL, Froehling D, Wahner-Roedler D, Trusko B, Welsh G, Ma H et al. NLP-based identification of pneumonia cases from free-text radiological reports. AMIA Annu Symp Proc 2008; 6: 172\u2013176.","journal-title":"AMIA Annu Symp Proc"},{"key":"BFtp2015182_CR11","first-page":"848","volume":"306","author":"HJ Murff","year":"2011","unstructured":"Murff HJ, FitzHenry F, Matheny ME, Gentry N, Kotter KL, Crimin K et al. Automated identification of postoperative complications within an electronic medical record using natural language processing. JAMA 2011; 306: 848\u2013855.","journal-title":"JAMA"},{"key":"BFtp2015182_CR12","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1136\/amiajnl-2011-000093","volume":"18","author":"V Garla","year":"2011","unstructured":"Garla V, Re VL III, Dorey-Stein Z, Kidwai F, Scotch M, Womack J et al. The Yale cTAKES extensions for document classification: architecture and application. J Am Med Inform Assoc 2011; 18: 614\u2013620.","journal-title":"J Am Med Inform Assoc"},{"key":"BFtp2015182_CR13","unstructured":"Ghassemi M, Naumann T, Joshi R, Rumshisky A Topic Models for Mortality Modeling in Intensive Care Units. Proceedings of the ICML Workshop on Machine Learning for Clinical Data Analysis; Edinburgh, Scotland, 2012."},{"key":"BFtp2015182_CR14","doi-asserted-by":"crossref","unstructured":"Ghassemi M, Naumann T, Doshi-Velez F, Brimmer N, Joshi R, Rumshisky A et al. (eds). Unfolding Physiological State: Mortality Modelling in Intensive Care Units. Proceedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2014); ACM: New York, NY, USA, 2014, pp 75\u201384.","DOI":"10.1145\/2623330.2623742"},{"key":"BFtp2015182_CR15","doi-asserted-by":"publisher","first-page":"e85733","DOI":"10.1371\/journal.pone.0085733","volume":"9","author":"C Poulin","year":"2014","unstructured":"Poulin C, Shiner B, Thompson P, Vepstas L, Young-Xu Y, Goertzel B et al. Predicting the risk of suicide by analyzing the text of clinical notes. PLoS One 2014; 9: e85733.","journal-title":"PLoS One"},{"key":"BFtp2015182_CR16","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1136\/jamia.2009.000893","volume":"17","author":"SN Murphy","year":"2010","unstructured":"Murphy SN, Weber G, Mendis M, Gainer V, Chueh HC, Churchill S et al. Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2). J Am Med Inform Assoc 2010; 17: 124\u2013130.","journal-title":"J Am Med Inform Assoc"},{"key":"BFtp2015182_CR17","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O et al. Scikit-learn: machine learning in Python. J Mach Learn Res 2011; 12: 2825\u20132830.","journal-title":"J Mach Learn Res"},{"key":"BFtp2015182_CR18","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1145\/361219.361220","volume":"18","author":"G Salton","year":"1975","unstructured":"Salton G, Wong A, Yang CS . A vector space model for automatic indexing. Commun ACM 1975; 18: 613\u2013620.","journal-title":"Commun ACM"},{"key":"BFtp2015182_CR19","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei DM, Ng AY, Jordan MI . Latent dirichlet allocation. J Mach Learn Res 2003; 3: 993\u20131022.","journal-title":"J Mach Learn Res"},{"key":"BFtp2015182_CR20","doi-asserted-by":"publisher","first-page":"5228","DOI":"10.1073\/pnas.0307752101","volume":"101","author":"TSM Griffiths","year":"2004","unstructured":"Griffiths TSM . Finding scientific topics. Proc Natl Acad Sci USA 2004; 101: 5228\u20135235.","journal-title":"Proc Natl Acad Sci USA"},{"key":"BFtp2015182_CR21","doi-asserted-by":"publisher","first-page":"1245","DOI":"10.1016\/0895-4356(94)90129-5","volume":"47","author":"M Charlson","year":"1994","unstructured":"Charlson M, Szatrowski TP, Peterson J, Gold J . Validation of a combined comorbidity index. J Clin Epidemiol 1994; 47: 1245\u20131251.","journal-title":"J Clin Epidemiol"},{"key":"BFtp2015182_CR22","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1016\/0021-9681(87)90171-8","volume":"40","author":"ME Charlson","year":"1987","unstructured":"Charlson ME, Pompei P, Ales KL, MacKenzie CR . A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987; 40: 373\u2013383.","journal-title":"J Chronic Dis"},{"key":"BFtp2015182_CR23","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1017\/S0033291711000997","volume":"42","author":"RH Perlis","year":"2012","unstructured":"Perlis RH, Iosifescu DV, Castro VM, Murphy SN, Gainer VS, Minnier J et al. Using electronic medical records to enable large-scale studies in psychiatry: treatment resistant depression as a model. Psychol Med 2012; 42: 41\u201350.","journal-title":"Psychol Med"},{"key":"BFtp2015182_CR24","first-page":"505","volume":"2012","author":"LSM Lehman","year":"2012","unstructured":"Lehman LSM, Long W, Lee J, Mark R . Risk stratification of ICU patients using topic models inferred from unstructured progress notes. AMIA Annu Symp Proc 2012; 2012: 505\u2013511.","journal-title":"AMIA Annu Symp Proc"},{"key":"BFtp2015182_CR25","doi-asserted-by":"publisher","first-page":"1445","DOI":"10.1176\/appi.ajp.2010.09111680","volume":"167","author":"GE Simon","year":"2010","unstructured":"Simon GE, Perlis RH . Personalized medicine for depression: can we match patients with treatments? Am J Psychiatry 2010; 167: 1445\u20131455.","journal-title":"Am J Psychiatry"},{"key":"BFtp2015182_CR26","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1197\/jamia.M3115","volume":"16","author":"O Uzuner","year":"2009","unstructured":"Uzuner O . Recognizing obesity and comorbidities in sparse data. J Am Med Inform Assoc 2009; 16: 561\u2013570.","journal-title":"J Am Med Inform Assoc"}],"container-title":["Translational Psychiatry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/tp2015182.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/tp2015182","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/tp2015182.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,4]],"date-time":"2023-01-04T03:52:22Z","timestamp":1672804342000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/tp2015182"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,10,18]]},"references-count":26,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2016,10]]}},"alternative-id":["BFtp2015182"],"URL":"https:\/\/doi.org\/10.1038\/tp.2015.182","relation":{},"ISSN":["2158-3188"],"issn-type":[{"value":"2158-3188","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,10,18]]},"assertion":[{"value":"1 May 2015","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 August 2015","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 September 2015","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 October 2016","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"RHP has served on advisory boards or provided consulting to AssureRx, Genomind, Healthrageous, Pamlab, Perfect Health, Pfizer, Psybrain and RIDVentures. The remaining authors declare no conflict of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}