乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T20:11:54Z","timestamp":1742933514927,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030757618"},{"type":"electronic","value":"9783030757625"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-75762-5_18","type":"book-chapter","created":{"date-parts":[[2021,5,8]],"date-time":"2021-05-08T09:07:43Z","timestamp":1620464863000},"page":"213-224","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Lifelong Learning Based Disease Diagnosis on Clinical Notes"],"prefix":"10.1007","author":[{"given":"Zifeng","family":"Wang","sequence":"first","affiliation":[]},{"given":"Yifan","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Rui","family":"Wen","sequence":"additional","affiliation":[]},{"given":"Xi","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Shao-Lun","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Yefeng","family":"Zheng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,5,9]]},"reference":[{"key":"18_CR1","doi-asserted-by":"crossref","unstructured":"Cao, S., Qian, B., Yin, C., Li, X., Wei, J., Zheng, Q., Davidson, I.: Knowledge guided short-text classification for healthcare applications. In: IEEE International Conference on Data Mining, pp. 31\u201340. IEEE (2017)","DOI":"10.1109\/ICDM.2017.12"},{"key":"18_CR2","unstructured":"Chaudhry, A., Ranzato, M., Rohrbach, M., Elhoseiny, M.: Efficient lifelong learning with a-gem. In: International Conference on Learning Representations (2018)"},{"key":"18_CR3","unstructured":"Choi, E., Bahadori, M.T., Schuetz, A., Stewart, W.F., Sun, J.: Doctor AI: predicting clinical events via recurrent neural networks. In: Machine Learning for Healthcare Conference, pp. 301\u2013318 (2016)"},{"key":"18_CR4","unstructured":"Choi, E., Bahadori, M.T., Sun, J., Kulas, J., Schuetz, A., Stewart, W.: RETAIN: an interpretable predictive model for healthcare using reverse time attention mechanism. In: Advances in Neural Information Processing Systems, pp. 3504\u20133512 (2016)"},{"key":"18_CR5","doi-asserted-by":"crossref","unstructured":"Hao, Y., et al.: An end-to-end model for question answering over knowledge base with cross-attention combining global knowledge. In: Annual Meeting of the Association for Computational Linguistics, pp. 221\u2013231 (2017)","DOI":"10.18653\/v1\/P17-1021"},{"key":"18_CR6","unstructured":"Huang, Z., Xu, W., Yu, K.: Bidirectional lstm-crf models for sequence tagging. arXiv preprint arXiv:1508.01991 (2015)"},{"key":"18_CR7","doi-asserted-by":"crossref","unstructured":"Joulin, A., Grave, E., Bojanowski, P., Mikolov, T.: Bag of tricks for efficient text classification. arXiv preprint arXiv:1607.01759 (2016)","DOI":"10.18653\/v1\/E17-2068"},{"issue":"13","key":"18_CR8","doi-asserted-by":"publisher","first-page":"3521","DOI":"10.1073\/pnas.1611835114","volume":"114","author":"J Kirkpatrick","year":"2017","unstructured":"Kirkpatrick, J., et al.: Overcoming catastrophic forgetting in neural networks. Proc. Natl. Acad. Sci. 114(13), 3521\u20133526 (2017)","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"6","key":"18_CR9","doi-asserted-by":"publisher","first-page":"e279","DOI":"10.1016\/S2589-7500(20)30102-3","volume":"2","author":"CS Lee","year":"2020","unstructured":"Lee, C.S., Lee, A.Y.: Clinical applications of continual learning machine learning. Lancet Digit Health 2(6), e279\u2013e281 (2020)","journal-title":"Lancet Digit Health"},{"key":"18_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/978-3-030-59710-8_17","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020","author":"Z Li","year":"2020","unstructured":"Li, Z., Zhong, C., Wang, R., Zheng, W.-S.: Continual learning of new diseases with dual distillation and ensemble strategy. In: Martel, A.L., et al. (eds.) MICCAI 2020. LNCS, vol. 12261, pp. 169\u2013178. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-59710-8_17"},{"key":"18_CR11","unstructured":"Lopez-Paz, D., Ranzato, M.: Gradient episodic memory for continual learning. In: Advances in Neural Information Processing Systems, pp. 6467\u20136476 (2017)"},{"key":"18_CR12","doi-asserted-by":"crossref","unstructured":"Ma, F., Chitta, R., Zhou, J., You, Q., Sun, T., Gao, J.: Dipole: diagnosis prediction in healthcare via attention-based bidirectional recurrent neural networks. In: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1903\u20131911 (2017)","DOI":"10.1145\/3097983.3098088"},{"key":"18_CR13","first-page":"2579","volume":"9","author":"LVD Maaten","year":"2008","unstructured":"Maaten, L.V.D., Hinton, G.: Visualizing data using t-sne. J. Mach. Learn. Res. 9, 2579\u20132605 (2008)","journal-title":"J. Mach. Learn. Res."},{"key":"18_CR14","unstructured":"de Masson d\u2019Autume, C., Ruder, S., Kong, L., Yogatama, D.: Episodic memory in lifelong language learning. In: Advances in Neural Information Processing Systems, pp. 13143\u201313152 (2019)"},{"issue":"3","key":"18_CR15","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1037\/0033-295X.102.3.419","volume":"102","author":"JL McClelland","year":"1995","unstructured":"McClelland, J.L., McNaughton, B.L., O\u2019Reilly, R.C.: Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. Psychol. Rev. 102(3), 419\u2013457 (1995)","journal-title":"Psychol. Rev."},{"issue":"2","key":"18_CR16","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1080\/09540099550039318","volume":"7","author":"A Robins","year":"1995","unstructured":"Robins, A.: Catastrophic forgetting, rehearsal and pseudorehearsal. Connect. Sci. 7(2), 123\u2013146 (1995)","journal-title":"Connect. Sci."},{"key":"18_CR17","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1007\/3-540-47922-8_8","volume-title":"Advances in Artificial Intelligence","author":"DL Silver","year":"2002","unstructured":"Silver, D.L., Mercer, R.E.: The task rehearsal method of life-long learning: overcoming impoverished data. In: Cohen, R., Spencer, B. (eds.) AI 2002. LNCS (LNAI), vol. 2338, pp. 90\u2013101. Springer, Heidelberg (2002). https:\/\/doi.org\/10.1007\/3-540-47922-8_8"},{"key":"18_CR18","doi-asserted-by":"crossref","unstructured":"Wang, H., Xiong, W., Yu, M., Guo, X., Chang, S., Wang, W.Y.: Sentence embedding alignment for lifelong relation extraction. In: International Conference of the North American Chapter of the Association for Computational Linguistics, pp. 796\u2013806 (2019)","DOI":"10.18653\/v1\/N19-1086"},{"key":"18_CR19","doi-asserted-by":"crossref","unstructured":"Wang, Z., et al.: Online disease self-diagnosis with inductive heterogeneous graph convolutional networks. In: Proceedings of The Web Conference 2021 (2021)","DOI":"10.1145\/3442381.3449795"},{"key":"18_CR20","doi-asserted-by":"crossref","unstructured":"Zhang, X., et al.: Learning robust patient representations from multi-modal electronic health records: a supervised deep learning approach. In: Proceedings of the SIAM International Conference on Data Mining (2021)","DOI":"10.1137\/1.9781611976700.66"}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-75762-5_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T17:14:19Z","timestamp":1710350059000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-75762-5_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030757618","9783030757625"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-75762-5_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"9 May 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 May 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 May 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/pakdd2021.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"673","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"157","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"23% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"7","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}