{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T17:05:44Z","timestamp":1774026344711,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,7,19]],"date-time":"2018-07-19T00:00:00Z","timestamp":1531958400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772110, 91546123, 71490724"],"award-info":[{"award-number":["61772110, 91546123, 71490724"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2017M620054"],"award-info":[{"award-number":["2017M620054"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key R&D Plan by the Ministry of Science and Technology of China","award":["2016YFC0901900"],"award-info":[{"award-number":["2016YFC0901900"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2018,7,19]]},"DOI":"10.1145\/3219819.3220095","type":"proceedings-article","created":{"date-parts":[[2018,7,19]],"date-time":"2018-07-19T13:05:12Z","timestamp":1532005512000},"page":"1608-1616","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":41,"title":["A Treatment Engine by Predicting Next-Period Prescriptions"],"prefix":"10.1145","author":[{"given":"Bo","family":"Jin","sequence":"first","affiliation":[{"name":"Dalian University of Technology, Dalian, China"}]},{"given":"Haoyu","family":"Yang","sequence":"additional","affiliation":[{"name":"Dalian University of Technology, Dalian, China"}]},{"given":"Leilei","family":"Sun","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Chuanren","family":"Liu","sequence":"additional","affiliation":[{"name":"Drexel University, Philadelphia, PA, USA"}]},{"given":"Yue","family":"Qu","sequence":"additional","affiliation":[{"name":"Dalian University of Technology, Dalian, China"}]},{"given":"Jianing","family":"Tong","sequence":"additional","affiliation":[{"name":"Tongji University, Shanghai, China"}]}],"member":"320","published-online":{"date-parts":[[2018,7,19]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"3rd Workshop on Data Mining for Medicine and Healthcare (DMMH), 14th SIAM International Conference on Data Mining (SDM","author":"Balasubramanian Arvind","year":"2014"},{"key":"e_1_3_2_2_2_1","unstructured":"The World Bank . 2016. Health Expenditure of the United States. http:\/\/data.worldbank.org\/indicator\/SH.XPD.TOTL.ZS?locations=US. (2016).  The World Bank . 2016. Health Expenditure of the United States. http:\/\/data.worldbank.org\/indicator\/SH.XPD.TOTL.ZS?locations=US. (2016)."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3097997"},{"key":"e_1_3_2_2_4_1","unstructured":"Vikas Chaurasia and Saurabh Pal . 2017. Data mining techniques: To predict and resolve breast cancer survivability. (2017).  Vikas Chaurasia and Saurabh Pal . 2017. Data mining techniques: To predict and resolve breast cancer survivability. (2017)."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783365"},{"key":"e_1_3_2_2_6_1","unstructured":"Edward Choi Mohammad Taha Bahadori Andy Schuetz Walter F Stewart and Jimeng Sun . 2016 a. Doctor ai: Predicting clinical events via recurrent neural networks Machine Learning for Healthcare Conference. 301--318.  Edward Choi Mohammad Taha Bahadori Andy Schuetz Walter F Stewart and Jimeng Sun . 2016 a. Doctor ai: Predicting clinical events via recurrent neural networks Machine Learning for Healthcare Conference. 301--318."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939823"},{"key":"e_1_3_2_2_8_1","unstructured":"Edward Choi Mohammad Taha Bahadori Jimeng Sun Joshua Kulas Andy Schuetz and Walter Stewart . 2016 c. Retain: An interpretable predictive model for healthcare using reverse time attention mechanism. In Advances in Neural Information Processing Systems. 3504--3512.   Edward Choi Mohammad Taha Bahadori Jimeng Sun Joshua Kulas Andy Schuetz and Walter Stewart . 2016 c. Retain: An interpretable predictive model for healthcare using reverse time attention mechanism. In Advances in Neural Information Processing Systems. 3504--3512."},{"key":"e_1_3_2_2_9_1","volume-title":"The Innovator's Prescription: A Disruptive Solution to the Healthcare Crisis","author":"Christensen Clayton","year":"2008"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098065"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICHI.2015.23"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICHI.2016.16"},{"key":"e_1_3_2_2_13_1","volume-title":"Temporal mining of integrated healthcare data: Methods, revealings and implications. SDM IW on data mining for medicine and healthcare","author":"Henriques Rui","year":"2013"},{"key":"e_1_3_2_2_14_1","volume-title":"et almbox","author":"Hochreiter Sepp","year":"2001"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_2_16_1","volume-title":"IJCAI 2017 Workshop on Artificial Intelligence in Affective Computing. 17--33","author":"Jaques Natasha","year":"2017"},{"key":"e_1_3_2_2_17_1","volume-title":"Leo Anthony Celi, and Roger G. Mark","author":"Johnson Alistair E. W.","year":"2016"},{"key":"e_1_3_2_2_18_1","unstructured":"Wonsung Lee Youngmin Lee Heeyoung Kim and Il-Chul Moon . 2016. Bayesian Nonparametric Collaborative Topic Poisson Factorization for Electronic Health Records-Based Phenotyping.. In IJCAI. 2544--2552.   Wonsung Lee Youngmin Lee Heeyoung Kim and Il-Chul Moon . 2016. Bayesian Nonparametric Collaborative Topic Poisson Factorization for Electronic Health Records-Based Phenotyping.. In IJCAI. 2544--2552."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3041021.3054200"},{"key":"e_1_3_2_2_20_1","volume-title":"Learning to Diagnose with LSTM Recurrent Neural Networks. Computer Science","author":"Lipton Zachary C","year":"2015"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098088"},{"key":"e_1_3_2_2_22_1","volume-title":"USA: ACM KDD Workshop on Connected Health in Big Data Era.","author":"Moskovitch Robert","year":"2014"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"crossref","unstructured":"Aaditya Prakash Siyuan Zhao Sadid A Hasan Vivek V Datla Kathy Lee Ashequl Qadir Joey Liu and Oladimeji Farri . 2017. Condensed Memory Networks for Clinical Diagnostic Inferencing. AAAI. 3274--3280.  Aaditya Prakash Siyuan Zhao Sadid A Hasan Vivek V Datla Kathy Lee Ashequl Qadir Joey Liu and Oladimeji Farri . 2017. Condensed Memory Networks for Clinical Diagnostic Inferencing. AAAI. 3274--3280.","DOI":"10.1609\/aaai.v31i1.10964"},{"key":"e_1_3_2_2_24_1","volume-title":"et almbox","author":"Rajkomar Alvin","year":"2018"},{"key":"e_1_3_2_2_25_1","volume-title":"A Bayesian Nonparametric Model for Disease Subtyping: Application to Emphysema Phenotypes","author":"Ross James C","year":"2017"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939866"},{"key":"e_1_3_2_2_27_1","volume-title":"IJCAI 2016-Workshop on Knowledge Discovery in Healthcare Data.","author":"Vasiljeva Ieva","year":"2016"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3127881"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098174"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2914683"},{"key":"e_1_3_2_2_31_1","volume-title":"Cross-people mobile-phone based activity recognition IJCAI","author":"Zhao Zhongtang"}],"event":{"name":"KDD '18: The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","location":"London United Kingdom","acronym":"KDD '18","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3219819.3220095","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3219819.3220095","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:07:30Z","timestamp":1750212450000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3219819.3220095"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,19]]},"references-count":31,"alternative-id":["10.1145\/3219819.3220095","10.1145\/3219819"],"URL":"https:\/\/doi.org\/10.1145\/3219819.3220095","relation":{},"subject":[],"published":{"date-parts":[[2018,7,19]]},"assertion":[{"value":"2018-07-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}