{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T11:53:45Z","timestamp":1743076425443,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":15,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811685309"},{"type":"electronic","value":"9789811685316"}],"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\/978-981-16-8531-6_5","type":"book-chapter","created":{"date-parts":[[2021,12,8]],"date-time":"2021-12-08T06:04:38Z","timestamp":1638943478000},"page":"62-71","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hospital Readmission Prediction Using Semantic Relations Between Medical Codes"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6410-8182","authenticated-orcid":false,"given":"Sea Jung","family":"Im","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1137-0272","authenticated-orcid":false,"given":"Yue","family":"Xu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8233-9195","authenticated-orcid":false,"given":"Jason","family":"Watson","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,12,9]]},"reference":[{"key":"5_CR1","unstructured":"Choi, E., Bahadori, M.T., Kulas, J.A., Schuetz, A., Stewart, W.F., Sun, J.: Retain: an interpretable predictive model for healthcare using reverse time attention mechanism. In: Advances in Neural Information Processing Systems, pp. 3504\u20133512 (2016)"},{"key":"5_CR2","unstructured":"Choi, E., Bahadori, M.T., Schuetz, A., Stewart, W.F., Sun, J.: Doctor AI: predicting clinical events via recurrent neural networks (2015)"},{"key":"5_CR3","doi-asserted-by":"crossref","unstructured":"Choi, E., et al.: Multi-layer representation learning for medical concepts. In: Proceedings of the 22nd ACM SIGKDD International Conference on knowledge discovery and data mining. KDD \u201916, vol. 13\u201317, pp. 1495\u20131504. ACM (2016)","DOI":"10.1145\/2939672.2939823"},{"key":"5_CR4","doi-asserted-by":"crossref","unstructured":"Choi, E., Bahadori, M.T., Song, L., Stewart, W., Sun, J.: Gram: Graph-based attention model for healthcare representation learning. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD \u201917, pp. 787\u2013795. ACM (2017)","DOI":"10.1145\/3097983.3098126"},{"key":"5_CR5","doi-asserted-by":"crossref","unstructured":"Esteban, C., Staeck, O., Baier, S., Yang, Y., Tresp, V.: Predicting clinical events by combining static and dynamic information using recurrent neural networks. In: Proceedings - 2016 IEEE International Conference on Healthcare Informatics, ICHI 2016, pp. 93\u2013101 (2016)","DOI":"10.1109\/ICHI.2016.16"},{"key":"5_CR6","doi-asserted-by":"crossref","unstructured":"Feng, Y., et al.: Patient outcome prediction via convolutional neural networks based on multi-granularity medical concept embedding. In: 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 770\u2013777. IEEE (2017)","DOI":"10.1109\/BIBM.2017.8217753"},{"key":"5_CR7","doi-asserted-by":"publisher","unstructured":"Goldberger, A.L., et al.: Physiobank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals. Circulation 101(23), e215\u2013e220 (2000). https:\/\/doi.org\/10.1161\/01.CIR.101.23.e215","DOI":"10.1161\/01.CIR.101.23.e215"},{"key":"5_CR8","unstructured":"of Library, W.H.O.O., Services, H.L.: Styles for bibliographic citations : guidelines for who-produced bibliographies (1988)"},{"key":"5_CR9","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: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery Data Mining, KDD \u201917, vol. 129685, pp. 1903\u20131911. ACM (2017)","DOI":"10.1145\/3097983.3098088"},{"key":"5_CR10","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space (2013). arXiv.org"},{"key":"5_CR11","doi-asserted-by":"crossref","unstructured":"Pham, T., Tran, T., Phung, D., Venkatesh, S.: Deepcare: a deep dynamic memory model for predictive medicine (2016)","DOI":"10.1007\/978-3-319-31750-2_3"},{"key":"5_CR12","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","volume":"20","author":"PJ Rousseeuw","year":"1987","unstructured":"Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J. Comp. Appl. Math. 20, 53\u201365 (1987). https:\/\/doi.org\/10.1016\/0377-0427(87)90125-7","journal-title":"J. Comp. Appl. Math."},{"key":"5_CR13","doi-asserted-by":"publisher","unstructured":"Venuthurupalli, S.K., Hoy, W.E., Healy, H.G., Cameron, A., Fassett, R.G.: CKD.QLD: establishment of a chronic kidney disease [CKD] registry in Queensland, Australia. BMC Nephrol. 18(1), 189 (2017). https:\/\/doi.org\/10.1186\/s12882-017-0607-5, https:\/\/www.ncbi.nlm.nih.gov\/pubmed\/28592254","DOI":"10.1186\/s12882-017-0607-5"},{"key":"5_CR14","doi-asserted-by":"publisher","unstructured":"Xiao, C., Ma, T., Dieng, A.B., Blei, D.M., Wang, F.: Readmission prediction via deep contextual embedding of clinical concepts. PLOS One 13(4), e0195024 (2018). https:\/\/doi.org\/10.1371\/journal.pone.0195024, https:\/\/www.ncbi.nlm.nih.gov\/pubmed\/29630604","DOI":"10.1371\/journal.pone.0195024"},{"key":"5_CR15","doi-asserted-by":"publisher","unstructured":"Zheng, B., Zhang, J., Yoon, S.W., Lam, S.S., Khasawneh, M., Poranki, S.: Predictive modeling of hospital readmissions using metaheuristics and data mining. Expert Syst. Appl. 42(20), 7110\u20137120 (2015). https:\/\/doi.org\/10.1016\/j.eswa.2015.04.066, http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417415003085","DOI":"10.1016\/j.eswa.2015.04.066"}],"container-title":["Communications in Computer and Information Science","Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-8531-6_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T15:07:45Z","timestamp":1648739265000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-8531-6_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9789811685309","9789811685316"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-8531-6_5","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"9 December 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AusDM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australasian Conference on Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brisbane, QLD","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 December 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ausdm2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ausdm21.ausdm.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}