{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T07:03:30Z","timestamp":1760425410517,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":27,"publisher":"ACM","license":[{"start":{"date-parts":[[2016,4,11]],"date-time":"2016-04-11T00:00:00Z","timestamp":1460332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"U.S General Services Administration","award":["Contract # GS-00-H-14-AA-C-094"],"award-info":[{"award-number":["Contract # GS-00-H-14-AA-C-094"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2016,4,11]]},"DOI":"10.1145\/2896338.2896347","type":"proceedings-article","created":{"date-parts":[[2016,4,12]],"date-time":"2016-04-12T12:23:12Z","timestamp":1460463792000},"page":"47-54","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Feature Importance and Predictive Modeling for Multi-source Healthcare Data with Missing Values"],"prefix":"10.1145","author":[{"given":"Karthik","family":"Srinivasan","sequence":"first","affiliation":[{"name":"University of Arizona, Tucson, AZ, USA"}]},{"given":"Faiz","family":"Currim","sequence":"additional","affiliation":[{"name":"University of Arizona, Tucson, AZ, USA"}]},{"given":"Sudha","family":"Ram","sequence":"additional","affiliation":[{"name":"University of Arizona, Tucson, AZ, USA"}]},{"given":"Casey","family":"Lindberg","sequence":"additional","affiliation":[{"name":"University of Arizona, Tucson, AZ, USA"}]},{"given":"Esther","family":"Sternberg","sequence":"additional","affiliation":[{"name":"University of Arizona, Tucson, AZ, USA"}]},{"given":"Perry","family":"Skeath","sequence":"additional","affiliation":[{"name":"University of Arizona, Tucson, AZ, USA"}]},{"given":"Bijan","family":"Najafi","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston, TX, USA"}]},{"given":"Javad","family":"Razjouyan","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston, TX, USA"}]},{"given":"Hyo-Ki","family":"Lee","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston, TX, USA"}]},{"given":"Colin","family":"Foe-Parker","sequence":"additional","affiliation":[{"name":"Aclima, Inc., San Francisco, CA, USA"}]},{"given":"Nicole","family":"Goebel","sequence":"additional","affiliation":[{"name":"Aclima, Inc., San Francisco, CA, USA"}]},{"given":"Reuben","family":"Herzl","sequence":"additional","affiliation":[{"name":"Aclima, Inc., San Francisco, CA, USA"}]},{"given":"Matthias R.","family":"Mehl","sequence":"additional","affiliation":[{"name":"University of Arizona, Tucson, AZ, USA"}]},{"given":"Brian","family":"Gilligan","sequence":"additional","affiliation":[{"name":"U. S. General Services Administration, Washington DC, DC, USA"}]},{"given":"Judith","family":"Heerwagen","sequence":"additional","affiliation":[{"name":"U. S. General Services Administration, Washington DC, DC, USA"}]},{"given":"Kevin","family":"Kampschroer","sequence":"additional","affiliation":[{"name":"U. S. General Services Administration, Washington DC, DC, USA"}]},{"given":"Kelli","family":"Canada","sequence":"additional","affiliation":[{"name":"U. S. General Services Administration, Washington DC, DC, USA"}]}],"member":"320","published-online":{"date-parts":[[2016,4,11]]},"reference":[{"volume-title":"Flexible Imputation of Missing Data","author":"Buuren S.","key":"e_1_3_2_1_1_1","unstructured":"Buuren , S. Van 2012. Flexible Imputation of Missing Data . CRC press . Buuren, S. Van 2012. Flexible Imputation of Missing Data. CRC press."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1080\/10629360600810434"},{"key":"e_1_3_2_1_3_1","first-page":"1","article-title":"Multivariate Imputation by Chained Equations","volume":"45","author":"Van Buuren S.","year":"2011","unstructured":"Van Buuren , S. and Groothuis-Oudshoorn , K. 2011 . Multivariate Imputation by Chained Equations . Journal Of Statistical Software. 45 , 3 (2011), 1 -- 67 . Van Buuren, S. and Groothuis-Oudshoorn, K. 2011. Multivariate Imputation by Chained Equations. Journal Of Statistical Software. 45, 3 (2011), 1--67.","journal-title":"Journal Of Statistical Software."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Chai T. and Draxler R.R. 2014. Root mean square error ( RMSE ) or mean absolute error ( MAE )? -- Arguments against avoiding RMSE in the literature. Geoscientific Model Development. (2014) 1247--1250.  Chai T. and Draxler R.R. 2014. Root mean square error ( RMSE ) or mean absolute error ( MAE )? -- Arguments against avoiding RMSE in the literature. Geoscientific Model Development. (2014) 1247--1250.","DOI":"10.5194\/gmd-7-1247-2014"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2012.09.003"},{"key":"e_1_3_2_1_6_1","unstructured":"D\u00edaz I. Hubbard A.E. Decker A. and Cohen M. 2013. Variable Importance and Prediction Methods for Longitudinal Problems with Missing Variables. (2013) 1--17.  D\u00edaz I. Hubbard A.E. Decker A. and Cohen M. 2013. Variable Importance and Prediction Methods for Longitudinal Problems with Missing Variables. (2013) 1--17."},{"volume-title":"Missing Data Analysis and Design","author":"Graham J.W.","key":"e_1_3_2_1_7_1","unstructured":"Graham , J.W. 2012. Missing Data Analysis and Design . Springer Science & Business Media . Graham, J.W. 2012. Missing Data Analysis and Design. Springer Science & Business Media."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.psych.58.110405.085530"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Hastie T. Tibshirani R. Friedman J. and Hastie Trevor Tibshirani Robert Friedman J. 2009. The Elements of Statistical Learning: Data Mining Inference and Prediction. The Mathematical Intelligencer.  Hastie T. Tibshirani R. Friedman J. and Hastie Trevor Tibshirani Robert Friedman J. 2009. The Elements of Statistical Learning: Data Mining Inference and Prediction. The Mathematical Intelligencer.","DOI":"10.1007\/978-0-387-84858-7"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1159\/000047359"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2009.03.016"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/0167-9473(93)E0056-A"},{"key":"e_1_3_2_1_13_1","unstructured":"Liaw A. and Wiener M. 2015. Package' randomForest'. Breiman and Cutler's random forests for classification and regression. CRAN Reference manual.  Liaw A. and Wiener M. 2015. Package' randomForest'. Breiman and Cutler's random forests for classification and regression. CRAN Reference manual."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1097\/PSY.0b013e31815a9230"},{"key":"e_1_3_2_1_15_1","volume-title":"Using Big Data for Predicting Freshmen Retention. Conference on Information Systems (ICIS)","author":"Ram S.","year":"2015","unstructured":"Ram , S. , Wang , Y. , Currim , F. and Currim , S . 2015 . Using Big Data for Predicting Freshmen Retention. Conference on Information Systems (ICIS) ( 2015 ). Ram, S., Wang, Y., Currim, F. and Currim, S. 2015. Using Big Data for Predicting Freshmen Retention. Conference on Information Systems (ICIS) (2015)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwq477"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1080\/00045608.2014.910072"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"Rubin D.B. 1976. Inference and missing data. Biometrika. 63(3) (1976) 581--592.  Rubin D.B. 1976. Inference and missing data. Biometrika. 63(3) (1976) 581--592.","DOI":"10.1093\/biomet\/63.3.581"},{"key":"e_1_3_2_1_19_1","unstructured":"Saar-tsechansky M. and Provost F. 2007. Handling Missing Values when Applying Classification Models. Journal of Machine Learning Research. 8 (2007) 1625--1657.   Saar-tsechansky M. and Provost F. 2007. Handling Missing Values when Applying Classification Models. Journal of Machine Learning Research. 8 (2007) 1625--1657."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2004.50"},{"key":"e_1_3_2_1_21_1","volume-title":"Combining Worthless Sensor Data. Measuring Mobile Emotions Workshop at MobileHCI.","author":"Setz C.","year":"2009","unstructured":"Setz , C. , Schumm , J. , Lorenz , C. , Arnrich , B. and Tr\u00f6ster , G . 2009 . Combining Worthless Sensor Data. Measuring Mobile Emotions Workshop at MobileHCI. ( 2009 ). Setz, C., Schumm, J., Lorenz, C., Arnrich, B. and Tr\u00f6ster, G. 2009. Combining Worthless Sensor Data. Measuring Mobile Emotions Workshop at MobileHCI. (2009)."},{"key":"e_1_3_2_1_22_1","volume-title":"To Explain or to Predict? Statistical science. 25, 3","author":"Shmueli G.","year":"2011","unstructured":"Shmueli , G. 2011. To Explain or to Predict? Statistical science. 25, 3 ( 2011 ), 289--310. Shmueli, G. 2011. To Explain or to Predict? Statistical science. 25, 3 (2011), 289--310."},{"key":"e_1_3_2_1_23_1","unstructured":"Sternberg E. Gilligan B. and Lindberg C. 2016. Health and Wellbeing in GSA Office Buildings and Beyond.  Sternberg E. Gilligan B. and Lindberg C. 2016. Health and Wellbeing in GSA Office Buildings and Beyond."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1097\/HJR.0b013e328336923a"},{"key":"e_1_3_2_1_25_1","first-page":"4","article-title":"Effects of the physical work environment on physiological measures of stress. European journal of cardiovascular prevention and rehabilitation?: official journal of the European Society of Cardiology","volume":"17","author":"Thayer J.F.","year":"2010","unstructured":"Thayer , J.F. , Verkuil , B. , Brosschot , J.F. , Kampschroer , K. , West , A. , Sterling , C. , Christie , I.C. , Abernethy , D.R. , Sollers , J.J. , Cizza , G. , Marques , A.H. and Sternberg , E.M. 2010 . Effects of the physical work environment on physiological measures of stress. European journal of cardiovascular prevention and rehabilitation?: official journal of the European Society of Cardiology , Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology. 17 , 4 (Aug. 2010), 431--9. Thayer, J.F., Verkuil, B., Brosschot, J.F., Kampschroer, K., West, A., Sterling, C., Christie, I.C., Abernethy, D.R., Sollers, J.J., Cizza, G., Marques, A.H. and Sternberg, E.M. 2010. Effects of the physical work environment on physiological measures of stress. European journal of cardiovascular prevention and rehabilitation?: official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology. 17, 4 (Aug. 2010), 431--9.","journal-title":"Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.25300\/MISQ\/2013\/37.1.02"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Yang S. Tian W. Heo Y. Meng Q. and Wei L. 2015. Variable Importance Analysis for Urban Building Energy Assessment in the Presence of Correlated Factors. Procedia Engineering. 121 (2015) 277--284.  Yang S. Tian W. Heo Y. Meng Q. and Wei L. 2015. Variable Importance Analysis for Urban Building Energy Assessment in the Presence of Correlated Factors. Procedia Engineering. 121 (2015) 277--284.","DOI":"10.1016\/j.proeng.2015.08.1069"}],"event":{"name":"DH '16: Digital Health 2016","sponsor":["UQAM Universit\u00e9 du Qu\u00e9bec \u00e0 Montr\u00e9al","SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","ACM Association for Computing Machinery"],"location":"Montr\u00e9al Qu\u00e9bec Canada","acronym":"DH '16"},"container-title":["Proceedings of the 6th International Conference on Digital Health Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2896338.2896347","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2896338.2896347","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T19:05:41Z","timestamp":1750273541000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2896338.2896347"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,4,11]]},"references-count":27,"alternative-id":["10.1145\/2896338.2896347","10.1145\/2896338"],"URL":"https:\/\/doi.org\/10.1145\/2896338.2896347","relation":{},"subject":[],"published":{"date-parts":[[2016,4,11]]},"assertion":[{"value":"2016-04-11","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}