{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T12:06:03Z","timestamp":1777550763301,"version":"3.51.4"},"reference-count":40,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2020A1515010924"],"award-info":[{"award-number":["2020A1515010924"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72101059"],"award-info":[{"award-number":["72101059"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Health Commission of China","award":["WKJ-ZJ-2102"],"award-info":[{"award-number":["WKJ-ZJ-2102"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["DIGITAL HEALTH"],"published-print":{"date-parts":[[2022,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Persistence of long-term COVID-19 pandemic is putting high pressure on healthcare services worldwide for several years. This article aims to establish models to predict infection levels and mortality of COVID-19 patients in China.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Machine learning models and deep learning models have been built based on the clinical features of COVID-19 patients. The best models are selected by area under the receiver operating characteristic curve (AUC) scores to construct two homogeneous ensemble models for predicting infection levels and mortality, respectively. The first-hand clinical data of 760 patients are collected from Zhongnan Hospital of Wuhan University between 3 January and 8 March 2020. We preprocess data with cleaning, imputation, and normalization.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Our models obtain AUC = 0.7059 and Recall (Weighted avg) = 0.7248 in predicting infection level, while AUC=0.8436 and Recall (Weighted avg) = 0.8486 in predicting mortality ratio. This study also identifies two sets of essential clinical features. One is C-reactive protein (CRP) or high sensitivity C-reactive protein (hs-CRP) and the other is chest tightness, age, and pleural effusion.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Two homogeneous ensemble models are proposed to predict infection levels and mortality of COVID-19 patients in China. New findings of clinical features for benefiting the machine learning models are reported. The evaluation of an actual dataset collected from January 3 to March 8, 2020 demonstrates the effectiveness of the models by comparing them with state-of-the-art models in prediction.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20552076221133692","type":"journal-article","created":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T02:06:46Z","timestamp":1667354806000},"page":"205520762211336","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Homogeneous ensemble models for predicting infection levels and mortality of COVID-19 patients: Evidence from China"],"prefix":"10.1177","volume":"8","author":[{"given":"Jiafeng","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Head, Neck and Thyroid Surgery, Zhejiang Provincial People's Hospital and People's Hospital Affiliated to Hangzhou Medical College, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianlong","family":"Zhou","sequence":"additional","affiliation":[{"name":"Emergency Center, Zhongnan Hospital of Wuhan University, Wuhan, China"},{"name":"Hubei Clinical Research Center for Emergency and Resuscitation, Zhongnan Hospital of Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3520-5052","authenticated-orcid":false,"given":"Zhitian","family":"Hou","sequence":"additional","affiliation":[{"name":"School of Computer Science, South China Normal University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoya","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Business Administration, Guangdong University of Finance & Economics, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yueyue","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Infectious Disease, Zhejiang Provincial People's Hospital and People's Hospital Affiliated to Hangzhou Medical College, Hangzhou, China"},{"name":"Graduate School of Clinical Medicine, Bengbu Medical College, Bengbu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shanshan","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Infectious Disease, Zhejiang Provincial People's Hospital and People's Hospital Affiliated to Hangzhou Medical College, Hangzhou, China"},{"name":"Graduate School of Clinical Medicine, Bengbu Medical College, Bengbu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Orthopaedic Surgery, Zhejiang Provincial People's Hospital and People's Hospital Affiliated to Hangzhou Medical College, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lina","family":"Shao","sequence":"additional","affiliation":[{"name":"Department of Nephrology, Zhejiang Provincial People's Hospital and People's Hospital Affiliated of Hangzhou Medical College, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rong","family":"Yan","sequence":"additional","affiliation":[{"name":"Department of Infectious Disease, Zhejiang Provincial People's Hospital and People's Hospital Affiliated to Hangzhou Medical College, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingshan","family":"Wang","sequence":"additional","affiliation":[{"name":"Graduate School of Clinical Medicine, Bengbu Medical College, Bengbu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minghua","family":"Ge","sequence":"additional","affiliation":[{"name":"Department of Head, Neck and Thyroid Surgery, Zhejiang Provincial People's Hospital and People's Hospital Affiliated to Hangzhou Medical College, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianyong","family":"Hao","sequence":"additional","affiliation":[{"name":"School of Computer Science, South China Normal University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuexing","family":"Tu","sequence":"additional","affiliation":[{"name":"Department of Intensive Care Unit, Zhejiang Provincial People's Hospital and People's Hospital Affiliated to Hangzhou Medical College, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haijun","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Infectious Disease, Zhejiang Provincial People's Hospital and People's Hospital Affiliated to Hangzhou Medical College, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2022,11,1]]},"reference":[{"key":"bibr1-20552076221133692","doi-asserted-by":"publisher","DOI":"10.2196\/21439"},{"key":"bibr2-20552076221133692","unstructured":"World Health Organization. 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