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Predicting Responders to Prone Positioning in Mechanically Ventilated Patients with COVID-19 Using Machine Learning

Tariq A. Dam,Luca F. Roggeveen,Fuda van Diggelen,Lucas M. Fleuren,Ameet R. Jagesar,Martijn Otten,Heder J. de Vries,Diederik Gommers,Olaf L. Cremer,Rob J. Bosman,Sander Rigter,Evert-Jan Wils,Tim Frenzel,Dave A. Dongelmans,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,Sesmu Arbous,Sebastiaan J. J. Vonk,Tomas Machado,Willem E. Herter,Harm-Jan de Grooth,Patrick J. Thoral,Armand R. J. Girbes,Mark Hoogendoorn,Paul W. G. Elbers

Annals of intensive care（2022）

引用 6|浏览51
关键词
COVID-19,Mechanical ventilation,Acute respiratory distress syndrome
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