{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T00:23:02Z","timestamp":1770337382635,"version":"3.49.0"},"publisher-location":"Basel Switzerland","reference-count":47,"publisher":"MDPI","license":[{"start":{"date-parts":[[2019,11,21]],"date-time":"2019-11-21T00:00:00Z","timestamp":1574294400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.3390\/proceedings2019031074","type":"proceedings-article","created":{"date-parts":[[2019,11,22]],"date-time":"2019-11-22T02:49:27Z","timestamp":1574390967000},"page":"74","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Predicting Health Care Costs Using Evidence Regression"],"prefix":"10.3390","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1440-8192","authenticated-orcid":false,"given":"Belisario","family":"Panay","sequence":"first","affiliation":[{"name":"Department of Computer Science, Universidad de Chile, 8370456 Santiago, Chile"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1608-6454","authenticated-orcid":false,"given":"Nelson","family":"Baloian","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Universidad de Chile, 8370456 Santiago, Chile"}]},{"given":"Jos\u00e9","family":"Pino","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Universidad de Chile, 8370456 Santiago, Chile"}]},{"given":"Sergio","family":"Pe\u00f1afiel","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Universidad de Chile, 8370456 Santiago, Chile"}]},{"given":"Horacio","family":"Sanson","sequence":"additional","affiliation":[{"name":"Allm Inc., Tokyo 150 0002, Japan"}]},{"given":"Nicolas","family":"Bersano","sequence":"additional","affiliation":[{"name":"Allm Inc., Tokyo 150 0002, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,21]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2018). Public Spending on Health: A Closer Look at Global Trends, Technical report."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2431","DOI":"10.1007\/s10916-011-9710-5","article-title":"Data mining in healthcare and biomedicine: A survey of the literature","volume":"36","author":"Yoo","year":"2012","journal-title":"J. Med. Syst."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1002\/hec.3003","article-title":"Measuring overfitting in nonlinear models: A new method and an application to health expenditures","volume":"24","author":"Bilger","year":"2015","journal-title":"Health Econ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1146\/annurev.publhealth.20.1.125","article-title":"Methods for analyzing health care utilization and costs","volume":"20","author":"Diehr","year":"1999","journal-title":"Ann. Rev. Public Health"},{"key":"ref_5","unstructured":"Kronick, R., Gilmer, T., Dreyfus, T., and Ganiats, T. (2002, June 24). CDPS-Medicare: The Chronic Illness and Disability Payment System Modified to Predict Expenditures for Medicare Beneficiaries; Final Report to CMS. Available online: http:\/\/www.hpm.umn.edu\/ambul_db\/db\/pdflibrary\/dbfile_91049.pdf."},{"key":"ref_6","first-page":"1312","article-title":"Supervised Learning Methods for Predicting Healthcare Costs: Systematic Literature Review and Empirical Evaluation","volume":"2017","author":"Morid","year":"2017","journal-title":"AMIA Ann. Symp. Proc."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0888-613X(03)00056-2","article-title":"Nonparametric regression analysis of uncertain and imprecise data using belief functions","volume":"35","year":"2004","journal-title":"Int. J. Approx. Reason."},{"key":"ref_8","unstructured":"Jones, A.M. (2009). Models for Health Care, University of York, Centre for Health Economics."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1002\/hec.1653","article-title":"Review of statistical methods for analysing healthcare resources and costs","volume":"20","author":"Mihaylova","year":"2011","journal-title":"Health Econ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/S0167-6296(98)00032-0","article-title":"Modeling risk using generalized linear models","volume":"18","author":"Blough","year":"1999","journal-title":"J. Health Econ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/0304-4076(94)01720-4","article-title":"On the choice between sample selection and two-part models","volume":"72","author":"Leung","year":"1996","journal-title":"J. Econometr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2716","DOI":"10.1002\/sim.2728","article-title":"Estimating the costs for a group of geriatric patients using the Coxian phase-type distribution","volume":"26","author":"Marshall","year":"2007","journal-title":"Stat. Med."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"677","DOI":"10.3346\/jkms.2004.19.5.677","article-title":"Comparison of hospital charge prediction models for colorectal cancer patients: neural network vs. decision tree models","volume":"19","author":"Lee","year":"2004","journal-title":"J. Korean Med. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1382","DOI":"10.1287\/opre.1080.0619","article-title":"Algorithmic prediction of health-care costs","volume":"56","author":"Bertsimas","year":"2008","journal-title":"Oper. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1017\/S1748499512000346","article-title":"Actuarial applications of multivariate two-part regression models","volume":"7","author":"Frees","year":"2013","journal-title":"Ann. Actuar. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Sushmita, S., Newman, S., Marquardt, J., Ram, P., Prasad, V., Cock, M.D., and Teredesai, A. (2015, January 18\u201320). Population cost prediction on public healthcare datasets. Proceedings of the 5th International Conference on Digital Health 2015, Florence, Italy.","DOI":"10.1145\/2750511.2750521"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1080\/10920277.2015.1110491","article-title":"Testing alternative regression frameworks for predictive modeling of health care costs","volume":"20","author":"Duncan","year":"2016","journal-title":"N. Am. Actuar. J."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"802","DOI":"10.1111\/j.1365-2656.2008.01390.x","article-title":"A working guide to boosted regression trees","volume":"77","author":"Elith","year":"2008","journal-title":"J. Anim. Ecol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/S0169-7161(04)24011-1","article-title":"Classification and regression trees, bagging, and boosting","volume":"24","author":"Sutton","year":"2005","journal-title":"Handb. Stat."},{"key":"ref_20","unstructured":"Zurada, J.M. (1992). Introduction to Artificial Neural Systems, West Publishing Company."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Breiman, L. (2017). Classification and Regression Trees, Routledge.","DOI":"10.1201\/9781315139470"},{"key":"ref_22","unstructured":"Lipton, Z.C. (2016). The mythos of model interpretability. arXiv."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Caruana, R., Lou, Y., Gehrke, J., Koch, P., Sturm, M., and Elhadad, N. (2015, January 10\u201315). Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission. Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, Australia.","DOI":"10.1145\/2783258.2788613"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1007\/s10994-015-5528-6","article-title":"Supersparse linear integer models for optimized medical scoring systems","volume":"102","author":"Ustun","year":"2016","journal-title":"Mach. Learn."},{"key":"ref_25","first-page":"290","article-title":"Prediction system for heart disease using Na\u00efve Bayes","volume":"3","author":"Pattekari","year":"2012","journal-title":"Int. J. Adv. Comput. Math. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1097\/00002820-199504000-00004","article-title":"Decision tree model describing alternate health care choices made by oncology patients","volume":"18","author":"Montbriand","year":"1995","journal-title":"Cancer Nurs."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1001\/jama.293.5.572","article-title":"Risk stratification for in-hospital mortality in acutely decompensated heart failure: Classification and regression tree analysis","volume":"293","author":"Fonarow","year":"2005","journal-title":"Jama"},{"key":"ref_28","first-page":"38","article-title":"Skin diseases expert system using Dempster-Shafer theory","volume":"4","author":"Maseleno","year":"2012","journal-title":"Int. J. Int. Syst. Appl."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Pe\u00f1afiel, S., Baloian, N., Pino, J.A., Quinteros, J., Riquelme, \u00c1., Sanson, H., and Teoh, D. (2018, January 11\u201314). Associating risks of getting strokes with data from health checkup records using Dempster-Shafer Theory. Proceedings of the 2018 IEEE 20th International Conference on Advanced Communication Technology (ICACT), Gang\u2019weondo, Korea.","DOI":"10.23919\/ICACT.2018.8323709"},{"key":"ref_30","unstructured":"Shrikumar, A., Greenside, P., and Kundaje, A. (2017). Learning important features through propagating activation differences. arXiv."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zeiler, M.D., and Fergus, R. (2014, January 6\u201312). Visualizing and understanding convolutional networks. Proceedings of the European Conference on Computer Vision, Zurich, Switzerland.","DOI":"10.1007\/978-3-319-10590-1_53"},{"key":"ref_32","unstructured":"Ribeiro, M.T., Singh, S., and Guestrin, C. (2016). Model-agnostic interpretability of machine learning. arXiv."},{"key":"ref_33","unstructured":"Craven, M., and Shavlik, J.W. (December, January 27). Extracting tree-structured representations of trained networks. Proceedings of the Advances in Neural Information Processing Systems, Denver, CO, USA."},{"key":"ref_34","first-page":"1803","article-title":"How to explain individual classification decisions","volume":"11","author":"Baehrens","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"ref_35","first-page":"1","article-title":"An efficient explanation of individual classifications using game theory","volume":"11","author":"Kononenko","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Krause, J., Perer, A., and Ng, K. (2016, January 7\u201312). Interacting with predictions: Visual inspection of black-box machine learning models. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, San Jose, CA, USA.","DOI":"10.1145\/2858036.2858529"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"931","DOI":"10.1038\/nmeth.3547","article-title":"Predicting effects of noncoding variants with deep learning\u2013based sequence model","volume":"12","author":"Zhou","year":"2015","journal-title":"Nat. Methods"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., and Guestrin, C. (2016, January 13\u201317). Why should i trust you?: Explaining the predictions of any classifier. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mmining, San Francisco, CA, USA.","DOI":"10.1145\/2939672.2939778"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Shafer, G. (1976). A Mathematical Theory of Evidence, Princeton University Press.","DOI":"10.1515\/9780691214696"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.ijar.2015.12.009","article-title":"Dempster\u2019s rule of combination","volume":"79","author":"Shafer","year":"2016","journal-title":"Int. J. Approx. Reason."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1016\/j.ymssp.2008.08.004","article-title":"Dempster\u2013Shafer regression for multi-step-ahead time-series prediction towards data-driven machinery prognosis","volume":"23","author":"Niu","year":"2009","journal-title":"Mechan. Syst. Signal Process."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1016\/j.eswa.2017.04.035","article-title":"Prediction of industrial equipment remaining useful life by fuzzy similarity and belief function theory","volume":"83","author":"Baraldi","year":"2017","journal-title":"Expert Syst. Appl."},{"key":"ref_43","unstructured":"World Health Organization (2001). International Classification of Functioning, Disability and Hhealth: ICF."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"804","DOI":"10.1109\/21.376493","article-title":"A k-nearest neighbor classification rule based on Dempster-Shafer theory","volume":"25","author":"Denoeux","year":"1995","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_45","unstructured":"Smets, P. (1994). What is Dempster-Shafer\u2019s model. Advances in the Dempster-Shafer Theory of Evidence, John Wiley & Sons, Inc."},{"key":"ref_46","unstructured":"Johnson, J., Douze, M., and J\u00e9gou, H. (2019). Billion-scale similarity search with GPUs. IEEE Trans. Big Data."},{"key":"ref_47","unstructured":"Lantz, B. (2013). Machine Learning with R, Packt Publishing Ltd."}],"event":{"name":"The International Conference on Ubiquitous Computing and Ambient \u202aIntelligence","acronym":"UCAmI 2019"},"container-title":["13th International Conference on Ubiquitous Computing and Ambient \u202aIntelligence UCAmI 2019\u202c"],"original-title":[],"link":[{"URL":"https:\/\/www.mdpi.com\/2504-3900\/31\/1\/74\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:36:13Z","timestamp":1760189773000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2504-3900\/31\/1\/74"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,21]]},"references-count":47,"alternative-id":["proceedings2019031074"],"URL":"https:\/\/doi.org\/10.3390\/proceedings2019031074","relation":{},"subject":[],"published":{"date-parts":[[2019,11,21]]}}}