{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T23:30:51Z","timestamp":1782948651140,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,7,25]]},"DOI":"10.1145\/3292500.3330779","type":"proceedings-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T13:17:26Z","timestamp":1564147046000},"page":"2487-2495","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":80,"title":["MetaPred"],"prefix":"10.1145","author":[{"given":"Xi Sheryl","family":"Zhang","sequence":"first","affiliation":[{"name":"Cornell University, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengyi","family":"Tang","sequence":"additional","affiliation":[{"name":"Michigan State University, East Lansing, MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiroko H.","family":"Dodge","sequence":"additional","affiliation":[{"name":"University of Michigan & Oregon Health & Science University, Ann Arbor, MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Michigan State University, East Lansing, MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fei","family":"Wang","sequence":"additional","affiliation":[{"name":"Cornell University, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Marcin Andrychowicz Misha Denil Sergio Gomez Matthew W Hoffman David Pfau Tom Schaul Brendan Shillingford and Nando De Freitas. 2016. Learning to learn by gradient descent by gradient descent. In NIPS .   Marcin Andrychowicz Misha Denil Sergio Gomez Matthew W Hoffman David Pfau Tom Schaul Brendan Shillingford and Nando De Freitas. 2016. Learning to learn by gradient descent by gradient descent. In NIPS ."},{"key":"e_1_3_2_1_2_1","volume-title":"Jamie Ryan Kiros, and Geoffrey E Hinton","author":"Ba Jimmy Lei","year":"2016"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3097997"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-009-5152-4"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007379606734"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788613"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098126"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocw112"},{"key":"e_1_3_2_1_9_1","volume-title":"Real-World Environments through Meta-Reinforcement Learning.","author":"Clavera Ignasi","year":"2018"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390177"},{"key":"e_1_3_2_1_11_1","volume-title":"Imagenet: A large-scale hierarchical image database. In CVPR .","author":"Deng Jia","year":"2009"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6639345"},{"key":"e_1_3_2_1_13_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018"},{"key":"e_1_3_2_1_14_1","volume-title":"Nature","volume":"542","author":"Esteva Andre","year":"2017"},{"key":"e_1_3_2_1_15_1","unstructured":"Chelsea Finn Pieter Abbeel and Sergey Levine. 2017a. Model-agnostic meta-learning for fast adaptation of deep networks. In ICML .   Chelsea Finn Pieter Abbeel and Sergey Levine. 2017a. Model-agnostic meta-learning for fast adaptation of deep networks. In ICML ."},{"key":"e_1_3_2_1_16_1","volume-title":"Conference on Robot Learning . 357--368","author":"Finn Chelsea","year":"2017"},{"key":"e_1_3_2_1_17_1","volume-title":"Victor OK Li, and Kyunghyun Cho","author":"Gu Jiatao","year":"2018"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.17216"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_20_1","volume-title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. In ICML .","author":"Ioffe Sergey","year":"2015"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrg3208"},{"key":"e_1_3_2_1_22_1","volume-title":"International journal of chronic obstructive pulmonary disease","author":"Kerkhof Marjan","year":"2015"},{"key":"e_1_3_2_1_23_1","volume-title":"Cell","volume":"172","author":"Kermany Daniel S","year":"2018"},{"key":"e_1_3_2_1_24_1","volume-title":"Convolutional neural networks for sentence classification. arXiv preprint arXiv:1408.5882","author":"Kim Yoon","year":"2014"},{"key":"e_1_3_2_1_25_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014"},{"key":"e_1_3_2_1_26_1","volume-title":"ICML deep learning workshop","author":"Koch Gregory"},{"key":"e_1_3_2_1_27_1","volume-title":"Science","volume":"350","author":"Lake Brenden M","year":"2015"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015382"},{"key":"e_1_3_2_1_29_1","volume-title":"Deep learning. nature","author":"LeCun Yann","year":"2015"},{"key":"e_1_3_2_1_30_1","volume-title":"Chan Ho So, and Jaewoo Kang","author":"Lee Jinhyuk","year":"2019"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"e_1_3_2_1_32_1","unstructured":"Sachin Ravi and Hugo Larochelle. 2016. Optimization as a model for few-shot learning. (2016).  Sachin Ravi and Hugo Larochelle. 2016. Optimization as a model for few-shot learning. (2016)."},{"key":"e_1_3_2_1_33_1","volume-title":"Been There","author":"Ritter Samuel"},{"key":"e_1_3_2_1_34_1","volume-title":"Predicting 30-day readmissions with preadmission electronic health record data. Medical care","author":"Shadmi Efrat","year":"2015"},{"key":"e_1_3_2_1_35_1","unstructured":"Jake Snell Kevin Swersky and Richard Zemel. 2017. Prototypical networks for few-shot learning. In NIPS .   Jake Snell Kevin Swersky and Richard Zemel. 2017. Prototypical networks for few-shot learning. In NIPS ."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219909"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"crossref","unstructured":"Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jon Shlens and Zbigniew Wojna. 2016. Rethinking the inception architecture for computer vision. In CVPR .  Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jon Shlens and Zbigniew Wojna. 2016. Rethinking the inception architecture for computer vision. In CVPR .","DOI":"10.1109\/CVPR.2016.308"},{"key":"e_1_3_2_1_38_1","volume-title":"Predictive modeling in urgent care: a comparative study of machine learning approaches. JAMIA Open","author":"Tang Fengyi","year":"2018"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"crossref","unstructured":"Sebastian Thrun and Lorien Pratt. 1998. Learning to learn: Introduction and overview. In Learning to learn .   Sebastian Thrun and Lorien Pratt. 1998. Learning to learn: Introduction and overview. In Learning to learn .","DOI":"10.1007\/978-1-4615-5529-2"},{"key":"e_1_3_2_1_40_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In NIPS .   Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In NIPS ."},{"key":"e_1_3_2_1_41_1","volume-title":"et almbox","author":"Vinyals Oriol","year":"2016"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339605"}],"event":{"name":"KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Anchorage AK USA","acronym":"KDD '19","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 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330779","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330779","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:57:51Z","timestamp":1750208271000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330779"}},"subtitle":["Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records"],"short-title":[],"issued":{"date-parts":[[2019,7,25]]},"references-count":42,"alternative-id":["10.1145\/3292500.3330779","10.1145\/3292500"],"URL":"https:\/\/doi.org\/10.1145\/3292500.3330779","relation":{},"subject":[],"published":{"date-parts":[[2019,7,25]]},"assertion":[{"value":"2019-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}