{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T16:54:50Z","timestamp":1782492890644,"version":"3.54.5"},"reference-count":48,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T00:00:00Z","timestamp":1564099200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Health Informatics J"],"published-print":{"date-parts":[[2020,6]]},"abstract":"<jats:p>Current mortality prediction models and scoring systems for intensive care unit patients are generally usable only after at least 24 or 48 h of admission, as some parameters are unclear at admission. However, some of the most relevant measurements are available shortly following admission. It is hypothesized that outcome prediction may be made using information available in the earliest phase of intensive care unit admission. This study aims to investigate how early hospital mortality can be predicted for intensive care unit patients. We conducted a thorough time-series analysis on the performance of different data mining methods during the first 48 h of intensive care unit admission. The results showed that the discrimination power of the machine-learning classification methods after 6 h of admission outperformed the main scoring systems used in intensive care medicine (Acute Physiology and Chronic Health Evaluation, Simplified Acute Physiology Score and Sequential Organ Failure Assessment) after 48 h of admission.<\/jats:p>","DOI":"10.1177\/1460458219850323","type":"journal-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T05:17:07Z","timestamp":1564118227000},"page":"1043-1059","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":50,"title":["Predicting hospital mortality for intensive care unit patients: Time-series analysis"],"prefix":"10.1177","volume":"26","author":[{"given":"Aya","family":"Awad","sequence":"first","affiliation":[{"name":"University of Portsmouth, UK; Arab Academy for Science and Technology, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1123-6823","authenticated-orcid":false,"given":"Mohamed","family":"Bader-El-Den","sequence":"additional","affiliation":[{"name":"University of Portsmouth, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"McNicholas","sequence":"additional","affiliation":[{"name":"Portsmouth Hospitals NHS Trust, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jim","family":"Briggs","sequence":"additional","affiliation":[{"name":"University of Portsmouth, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasser","family":"El-Sonbaty","sequence":"additional","affiliation":[{"name":"Arab Academy for Science and Technology, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2019,7,26]]},"reference":[{"key":"bibr1-1460458219850323","volume-title":"Proceedings of the thirtieth AAAI conference on artificial intelligence","author":"Luo Y","year":"2016"},{"key":"bibr2-1460458219850323","doi-asserted-by":"publisher","DOI":"10.3390\/jpm2040138"},{"key":"bibr3-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1016\/S2213-2600(14)70239-5"},{"key":"bibr4-1460458219850323","first-page":"100","volume-title":"Proceedings of the annual international conference of the IEEE in Engineering in Medicine and Biology Society (EMBC)","author":"Ribas VJ"},{"key":"bibr5-1460458219850323","doi-asserted-by":"publisher","DOI":"10.4258\/hir.2011.17.4.232"},{"key":"bibr6-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2004.07.002"},{"key":"bibr7-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0142(20000501)88:9<2105::AID-CNCR16>3.0.CO;2-3"},{"key":"bibr8-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1097\/00003246-198411000-00012"},{"key":"bibr9-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1097\/00003246-198510000-00009"},{"key":"bibr10-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1001\/jama.1993.03510200084037"},{"key":"bibr11-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1007\/BF01709751"},{"key":"bibr12-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1001\/jama.1993.03510240069035"},{"key":"bibr13-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1097\/00003246-199811000-00016"},{"key":"bibr14-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1007\/s00134-012-2578-0"},{"key":"bibr15-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1097\/00075198-200208000-00009"},{"key":"bibr16-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(10)60575-2"},{"key":"bibr17-1460458219850323","doi-asserted-by":"publisher","DOI":"10.4103\/0300-1652.129651"},{"key":"bibr18-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1378\/chest.100.6.1619"},{"key":"bibr19-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1186\/cc3821"},{"key":"bibr20-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1007\/s00134-008-1286-2"},{"key":"bibr21-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1007\/s00134-005-2763-5"},{"key":"bibr22-1460458219850323","first-page":"2464","volume-title":"Proceedings of the 38th annual international conference of the Engineering in Medicine and Biology Society (EMBC)","author":"Hoogendoorn M"},{"key":"bibr23-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1177\/0951484817696212"},{"key":"bibr24-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2017.10.002"},{"key":"bibr25-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1097\/01.CCM.0000215112.84523.F0"},{"key":"bibr26-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1097\/CCM.0b013e3182a66a49"},{"key":"bibr27-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1097\/01.CCM.0000257337.63529.9F"},{"key":"bibr28-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1097\/00003246-198507000-00001"},{"key":"bibr29-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1016\/j.amsu.2016.09.002"},{"key":"bibr30-1460458219850323","doi-asserted-by":"crossref","unstructured":"Sadeghi R, Banerjee T, Romine W. Early hospital mortality prediction using vital signals, 2018, https:\/\/arxiv.org\/abs\/1803.06589","DOI":"10.1016\/j.smhl.2018.07.001"},{"key":"bibr31-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2006.12.002"},{"key":"bibr32-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1016\/S0735-1097(18)30783-6"},{"key":"bibr33-1460458219850323","first-page":"257","volume-title":"Proceedings of the computing in cardiology (CINC)","author":"Citi L"},{"key":"bibr34-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2018.02.008"},{"key":"bibr35-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1177\/0885066615585951"},{"key":"bibr36-1460458219850323","volume-title":"Data mining techniques: for marketing, sales, and customer support","author":"Berry MJ","year":"1997"},{"key":"bibr37-1460458219850323","first-page":"680","volume-title":"Proceedings of the IEEE congress on evolutionary computation (CEC)","author":"Perry T"},{"key":"bibr38-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1145\/1656274.1656278"},{"key":"bibr39-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"bibr40-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1097\/CCM.0b013e31820a92c6"},{"key":"bibr41-1460458219850323","doi-asserted-by":"publisher","DOI":"10.19026\/rjaset.5.5044"},{"key":"bibr42-1460458219850323","first-page":"640","volume-title":"Proceedings of the 2014 IEEE\/ACS 11th international conference on computer systems and applications (AICCSA)","author":"Bader-El-Den M."},{"key":"bibr43-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-14-106"},{"key":"bibr44-1460458219850323","volume-title":"Proceedings of the 2006 8th international conference on signal processing","volume":"3","author":"Wang J"},{"key":"bibr45-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2878400"},{"key":"bibr46-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2018.05.001"},{"key":"bibr47-1460458219850323","volume-title":"Statistics: methods and applications: a comprehensive reference for science, industry, and data mining","author":"Hill T","year":"2006"},{"key":"bibr48-1460458219850323","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2016.35"}],"container-title":["Health Informatics Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/1460458219850323","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/1460458219850323","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/1460458219850323","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T22:30:37Z","timestamp":1777501837000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/1460458219850323"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,26]]},"references-count":48,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,6]]}},"alternative-id":["10.1177\/1460458219850323"],"URL":"https:\/\/doi.org\/10.1177\/1460458219850323","relation":{},"ISSN":["1460-4582","1741-2811"],"issn-type":[{"value":"1460-4582","type":"print"},{"value":"1741-2811","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,26]]}}}