{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T22:02:54Z","timestamp":1764194574906},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2021,5,27]],"date-time":"2021-05-27T00:00:00Z","timestamp":1622073600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,27]]},"abstract":"<jats:p>The ongoing COVID-19 pandemic has become the most impactful pandemic of the past century. The SARS-CoV-2 virus has spread rapidly across the globe affecting and straining global health systems. More than 2 million people have died from COVID-19 (as of 30 January 2021). To lessen the pandemic\u2019s impact, advanced methods such as Artificial Intelligence models are proposed to predict mortality, morbidity, disease severity, and other outcomes and sequelae. We performed a rapid scoping literature review to identify the deep learning techniques that have been applied to predict hospital mortality in COVID-19 patients. Our review findings provide insights on the important deep learning models, data types, and features that have been reported in the literature. These summary findings will help scientists build reliable and accurate models for better intervention strategies for predicting mortality in current and future pandemic situations.<\/jats:p>","DOI":"10.3233\/shti210285","type":"book-chapter","created":{"date-parts":[[2021,5,27]],"date-time":"2021-05-27T14:06:07Z","timestamp":1622124367000},"source":"Crossref","is-referenced-by-count":3,"title":["Deep Learning Methods to Predict Mortality in COVID-19 Patients: A Rapid Scoping Review"],"prefix":"10.3233","author":[{"given":"Mahanazuddin","family":"Syed","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA"}]},{"given":"Shorabuddin","family":"Syed","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA"}]},{"given":"Kevin","family":"Sexton","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA"}]},{"given":"Melody L.","family":"Greer","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA"}]},{"given":"Meredith","family":"Zozus","sequence":"additional","affiliation":[{"name":"Department of Population Health Sciences, University of Texas Health Science, Center at San Antonio, San Antonio, TX, USA"}]},{"given":"Sudeepa","family":"Bhattacharyya","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences and Arkansas Biosciences Institute, Arkansas State University, Jonesboro, AR, USA"}]},{"given":"Farhanuddin","family":"Syed","sequence":"additional","affiliation":[{"name":"College of Medicine, Shadan Institute of Medical Sciences, Hyderabad, TS, IN"}]},{"given":"Fred","family":"Prior","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Public Health and Informatics"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI210285","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,25]],"date-time":"2021-10-25T13:14:57Z","timestamp":1635167697000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI210285"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,27]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti210285","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,27]]}}}