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Assessing the prognostic utility of clinical and radiomic features for COVID-19 patients admitted to ICU: challenges and lessons learned.

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第一作者： Yuming,Sun

第一单位： Biostatistics, University of Michigan, Ann Arbor, MI.

作者： Yuming,Sun ^[1] ; Stephen,Salerno ^[1] ; Ziyang,Pan ^[1] ; Eileen,Yang ^[1] ; Chinakorn,Sujimongkol ^[1] ; Jiyeon,Song ^[1] ; Xinan,Wang ^[2] ; Peisong,Han ^[1] ; Donglin,Zeng ^[1] ; Jian,Kang ^[1] ; David C,Christiani ^[2] ; Yi,Li ^[1]

作者单位： Biostatistics, University of Michigan, Ann Arbor, MI. ^[1] Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA. ^[2]

关键词 COVID-19 X-ray imaging machine learning survival prediction

DOI 10.1162/99608f92.9d86a749

PMID 38974963

发布时间 2025-07-19

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Assessing the prognostic utility of clinical and radiomic features for COVID-19 patients admitted to ICU: challenges and lessons learned.

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Assessing the prognostic utility of clinical and radiomic features for COVID-19 patients admitted to ICU: challenges and lessons learned.

Harvard data science review

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Harvard data science review

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