{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:31:27Z","timestamp":1750221087874,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":29,"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"}],"funder":[{"name":"National Institutes of Health (NIH)","award":["HL125089"],"award-info":[{"award-number":["HL125089"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,7,25]]},"DOI":"10.1145\/3292500.3330770","type":"proceedings-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T13:17:26Z","timestamp":1564147046000},"page":"2547-2555","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Naranjo Question Answering using End-to-End Multi-task Learning Model"],"prefix":"10.1145","author":[{"given":"Bhanu Pratap Singh","family":"Rawat","sequence":"first","affiliation":[{"name":"University of Massachusetts Amherst, Amherst, MA, USA"}]},{"given":"Fei","family":"Li","sequence":"additional","affiliation":[{"name":"University of Massachusetts Lowell, Lowell, MA, USA"}]},{"given":"Hong","family":"Yu","sequence":"additional","affiliation":[{"name":"University of Massachusetts Lowell, Lowell, MA, USA"}]}],"member":"320","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"volume-title":"Adverse drug reaction monitoring in a secondary care hospital in South India. British journal of clinical pharmacology 65, 2","year":"2008","author":"Arulmani R","key":"e_1_3_2_2_1_1"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.1997.03540280045032"},{"volume-title":"Question answering with subgraph embeddings. arXiv preprint arXiv:1406.3676","year":"2014","author":"Bordes Antoine","key":"e_1_3_2_2_3_1"},{"volume-title":"Largescale simple question answering with memory networks. arXiv preprint arXiv:1506.02075","year":"2015","author":"Bordes Antoine","key":"e_1_3_2_2_4_1"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007379606734"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.1997.03540280039031"},{"volume-title":"Global trigger tool 'shows that adverse events in hospitals may be ten times greater than previously measured. Health affairs 30, 4","year":"2011","author":"Classen David C","key":"e_1_3_2_2_7_1"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2710.2006.00744.x"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0004439"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788608"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2005.06.042"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1882992.1883008"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2015.08.013"},{"key":"e_1_3_2_2_14_1","unstructured":"Trung Huynh Yulan He Alistair Willis and Stefan R\u00fcger. 2016. Adverse drug reaction classification with deep neural networks. Coling.  Trung Huynh Yulan He Alistair Willis and Stefan R\u00fcger. 2016. Adverse drug reaction classification with deep neural networks. Coling."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-1056"},{"volume-title":"Adverse events in hospitals: national incidence among Medicare beneficiaries","year":"2010","author":"Levinson Daniel R","key":"e_1_3_2_2_16_1"},{"volume-title":"Extraction of information related to adverse drug events from electronic health record notes: design of an end-to-end model based on deep learning. JMIR medical informatics 6, 4","year":"2018","author":"Li Fei","key":"e_1_3_2_2_17_1"},{"volume-title":"Medication-related adverse outcomes in US hospitals and emergency departments","year":"2008","author":"Lucado Jennifer","key":"e_1_3_2_2_18_1"},{"volume-title":"Effective approaches to attention-based neural machine translation. arXiv preprint arXiv:1508.04025","year":"2015","author":"Luong Minh-Thang","key":"e_1_3_2_2_19_1"},{"volume-title":"Question answering through transfer learning from large fine-grained supervision data. arXiv preprint arXiv:1702.02171","year":"2017","author":"Min Sewon","key":"e_1_3_2_2_20_1"},{"volume-title":"Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning. JMIR public health and surveillance 4, 2","year":"2018","author":"Munkhdalai Tsendsuren","key":"e_1_3_2_2_21_1"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1038\/clpt.1981.154"},{"volume-title":"Adverse drug reactions in an elderly hospitalised population. Drugs & aging 22, 9","year":"2005","author":"Passarelli Maria Cristina G","key":"e_1_3_2_2_23_1"},{"volume-title":"Maximum likelihood estimation for the negative binomial dispersion parameter. Biometrics","year":"1990","author":"Piegorsch Walter W","key":"e_1_3_2_2_24_1"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.4103\/0976-500X.85957"},{"volume-title":"Bidirectional attention flow for machine comprehension. arXiv preprint arXiv:1611.01603","year":"2016","author":"Seo Minjoon","key":"e_1_3_2_2_26_1"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339712"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1018"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2006.17"}],"event":{"name":"KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Anchorage AK USA","acronym":"KDD '19"},"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\/3292500.3330770","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330770","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\/3292500.3330770"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,25]]},"references-count":29,"alternative-id":["10.1145\/3292500.3330770","10.1145\/3292500"],"URL":"https:\/\/doi.org\/10.1145\/3292500.3330770","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"}}]}}