{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T20:32:04Z","timestamp":1777321924867,"version":"3.51.4"},"reference-count":63,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2017,2,8]],"date-time":"2017-02-08T00:00:00Z","timestamp":1486512000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"University of Virginia Hobby Postdoctoral and Predoctoral Fellowships in Computational Science"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Intell. Syst. Technol."],"published-print":{"date-parts":[[2017,5,31]]},"abstract":"<jats:p>Electronic health records (EHR) provide a rich source of temporal data that present a unique opportunity to characterize disease patterns and risk of imminent disease. While many data-mining tools have been adopted for EHR-based disease early detection, linear discriminant analysis (LDA) is one of the most commonly used statistical methods. However, it is difficult to train an accurate LDA model for early disease diagnosis when too few patients are known to have the target disease. Furthermore, EHR data are heterogeneous with significant noise. In such cases, the covariance matrices used in LDA are usually singular and estimated with a large variance.<\/jats:p>\n          <jats:p>\n            This article presents\n            <jats:italic>Daehr<\/jats:italic>\n            , an extension of the LDA framework using electronic health record data to address these issues. Beyond existing LDA analyzers, we propose\n            <jats:italic>Daehr<\/jats:italic>\n            to (1) eliminate the data noise caused by the manual encoding of EHR data and (2) lower the variance of parameter (covariance matrices) estimation for LDA models when only a few patients\u2019 EHR are available for training. To achieve these two goals, we designed an iterative algorithm to improve the covariance matrix estimation with embedded data-noise\/parameter-variance reduction for LDA. We evaluated\n            <jats:italic>Daehr<\/jats:italic>\n            extensively using the College Health Surveillance Network, a large, real-world EHR dataset. Specifically, our experiments compared the performance of LDA to three baselines (i.e., LDA and its derivatives) in identifying college students at high risk for mental health disorders from 23 U.S. universities. Experimental results demonstrate\n            <jats:italic>Daehr<\/jats:italic>\n            significantly outperforms the three baselines by achieving 1.4%--19.4% higher accuracy and a 7.5%--43.5% higher F1-score.\n          <\/jats:p>","DOI":"10.1145\/3007195","type":"journal-article","created":{"date-parts":[[2017,2,10]],"date-time":"2017-02-10T13:28:54Z","timestamp":1486733334000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["<i>Daehr<\/i>"],"prefix":"10.1145","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5451-3253","authenticated-orcid":false,"given":"Haoyi","family":"Xiong","sequence":"first","affiliation":[{"name":"Missouri University of Science and Technology, Missouri, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinghe","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Virginia, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Huang","sequence":"additional","affiliation":[{"name":"University of Virginia, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kevin","family":"Leach","sequence":"additional","affiliation":[{"name":"University of Virginia, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laura E.","family":"Barnes","sequence":"additional","affiliation":[{"name":"University of Virginia, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,2,8]]},"reference":[{"key":"e_1_2_2_1_1","unstructured":"2012. CMS: Electronic Health Records. Retrieved from https:\/\/www.cms.gov\/Medicare\/E-health\/EHealthRecords\/index.html.  2012. CMS: Electronic Health Records. Retrieved from https:\/\/www.cms.gov\/Medicare\/E-health\/EHealthRecords\/index.html."},{"key":"e_1_2_2_2_1","volume-title":"Any Mental Illness (AMI) Among Adults"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1097\/MLR.0b013e3181ef60d9"},{"key":"e_1_2_2_4_1","volume-title":"American college health association national college health assessment","author":"American College Health Association. 2014.","year":"2014"},{"key":"e_1_2_2_5_1","volume-title":"Statistical Decision Theory and Bayesian Analysis","author":"Berger James O."},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/0041-5553(67)90040-7"},{"key":"e_1_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.5705\/ss.2010.253"},{"key":"e_1_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273514"},{"key":"e_1_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1090\/S0002-9939-1959-0105008-8"},{"key":"e_1_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1198\/TECH.2011.08118"},{"key":"e_1_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.286.2.180"},{"key":"e_1_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.3201\/eid1210.060016"},{"key":"e_1_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1137\/9781611971941"},{"key":"e_1_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-1809.1936.tb02137.x"},{"key":"e_1_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2005.11.016"},{"key":"e_1_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-015-0216-9"},{"key":"e_1_2_2_17_1","volume-title":"Michael J. Pencina, and John P. A. Ioannidis.","author":"Goldstein Benjamin A.","year":"2016"},{"key":"e_1_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2014.01.007"},{"key":"e_1_2_2_19_1","volume-title":"Appendix A - Clinical Classification Software-DIAGNOSES (January 1980 through","author":"HCUP.","year":"2014"},{"key":"e_1_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1093\/imanum\/22.3.329"},{"key":"e_1_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.33.2.25"},{"key":"e_1_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.5555\/839291.842812"},{"key":"e_1_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1136\/amiajnl-2014-002733"},{"key":"e_1_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1136\/amiajnl-2014-002733"},{"key":"e_1_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrg3208"},{"key":"e_1_2_2_26_1","volume-title":"Proceedings of the 5th European Conference on Principles and Practice of Knowledge Discovery in Databases.","author":"Jensen Susan","year":"2001"},{"key":"e_1_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.24105\/ejbi.2013.09.1.2"},{"key":"e_1_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICHI.2014.10"},{"key":"e_1_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1001\/archpsyc.60.8.789"},{"key":"e_1_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.3928\/0048-5713-20020901-06"},{"key":"e_1_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.2337\/diacare.26.3.725"},{"key":"e_1_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783352"},{"key":"e_1_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2002.806647"},{"key":"e_1_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1186\/1756-0500-4-299"},{"key":"e_1_2_2_35_1","doi-asserted-by":"crossref","volume-title":"Discriminant Analysis and Statistical Pattern Recognition","author":"McLachlan Geoffrey","DOI":"10.1002\/0471725293"},{"key":"e_1_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/SIEDS.2016.7489280"},{"key":"e_1_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-8853-9"},{"key":"e_1_2_2_38_1","volume-title":"Personalized predictive modeling and risk factor identification using patient similarity. AMIA Summit on Clinical Research Informatics (CRI)","author":"Ng Kenney","year":"2015"},{"key":"e_1_2_2_39_1","volume-title":"AMIA Summits on Translational Science Proceedings 2015 (March","author":"Ng Kenney","year":"2015"},{"key":"e_1_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2015.7364060"},{"key":"e_1_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/2557500.2557508"},{"key":"e_1_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2015.06.020"},{"key":"e_1_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0401736101"},{"key":"e_1_2_2_44_1","volume-title":"Proceeding of the World Congress on Engineering","volume":"2","author":"Qiao Zhihua"},{"key":"e_1_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1214\/10-AOS870"},{"key":"e_1_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.e3318"},{"key":"e_1_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/2408736.2408740"},{"key":"e_1_2_2_48_1","unstructured":"Barbara G. Tabachnick Linda S. Fidell and others. 2001. Using multivariate statistics. (2001). 530--538.  Barbara G. Tabachnick Linda S. Fidell and others. 2001. Using multivariate statistics. (2001). 530--538."},{"key":"e_1_2_2_49_1","volume-title":"Turner and Adrienne Keller","author":"James","year":"2015"},{"key":"e_1_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.4088\/PCC.v07n0405"},{"key":"e_1_2_2_51_1","volume-title":"Functional Operators: The Geometry of Orthogonal Spaces","author":"Neumann John Von","year":"1951"},{"key":"e_1_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339605"},{"key":"e_1_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.111"},{"key":"e_1_2_2_54_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2015.2425365"},{"key":"e_1_2_2_55_1","volume-title":"AMIA Annual Symposium Proceedings","volume":"2014","author":"Wang Fei","year":"2014"},{"key":"e_1_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.31887\/DCNS.2003.5.2\/huwittchen"},{"key":"e_1_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2008.03.012"},{"key":"e_1_2_2_58_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2012.725386"},{"key":"e_1_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2004.37"},{"key":"e_1_2_2_60_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-011-9710-5"},{"key":"e_1_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2015.7364054"},{"key":"e_1_2_2_62_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.04.066"},{"key":"e_1_2_2_63_1","doi-asserted-by":"publisher","DOI":"10.1198\/tech.2003.s33"}],"container-title":["ACM Transactions on Intelligent Systems and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3007195","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3007195","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:23:41Z","timestamp":1750220621000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3007195"}},"subtitle":["A Discriminant Analysis Framework for Electronic Health Record Data and an Application to Early Detection of Mental Health Disorders"],"short-title":[],"issued":{"date-parts":[[2017,2,8]]},"references-count":63,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2017,5,31]]}},"alternative-id":["10.1145\/3007195"],"URL":"https:\/\/doi.org\/10.1145\/3007195","relation":{},"ISSN":["2157-6904","2157-6912"],"issn-type":[{"value":"2157-6904","type":"print"},{"value":"2157-6912","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,2,8]]},"assertion":[{"value":"2015-12-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2016-10-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2017-02-08","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}