Assess and Validate Predictive Performance of Models for In-Hospital Mortality in COVID-19 Patients: A Retrospective Cohort Study in the Netherlands Comparing the Value of Registry Data with High-Granular Electronic Health Records.

Iacopo Vagliano,Martijn C. Schut,Ameen Abu-Hanna,Dave A. Dongelmans,Dylan W. de Lange,Diederik Gommers,Olaf L. Cremer,Rob J. Bosman,Sander Rigter,Evert-Jan Wils,Tim Frenzel,Remko de Jong,Marco A. A. Peters,Marlijn J. A. Kamps,Dharmanand Ramnarain,Ralph Nowitzky,Fleur G. C. A. Nooteboom,Wouter de Ruijter,Louise C. Urlings-Strop,Ellen G. M. Smit,D. Jannet Mehagnoul-Schipper,Tom Dormans,Cornelis P. C. de Jager,Stefaan H. A. Hendriks,Sefanja Achterberg,Evelien Oostdijk,Auke C. Reidinga,Barbara Festen-Spanjer,Gert B. Brunnekreef,Alexander D. Cornet,Walter van den Tempel,Age D. Boelens,Peter Koetsier,Judith Lens,Harald J. Faber,A. Karakus,Robert Entjes,Paul de Jong,Thijs C. D. Rettig, M. C. Reuland,Sesmu Arbous,Lucas M. Fleuren,Tariq A. Dam,Patrick J. Thoral,Robbert C. A. Lalisang,Michele Tonutti,Daan P. de Bruin,Paul W. G. Elbers,Nicolette F. de Keizer

International Journal of Medical Informatics（2022）

Cited 5|Views37

Key words

Covid-19 [C01.748.610.763.500],Critical care [E02.760.190],In-hospital mortality,[E05.318.308.985.550.400],Prognosis [E01.789],Machine learning [G17.035.250.500],Electronic Health Record,[E05.318.308.940.968.625.500]

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