Developing and validating machine learning models to predict next-day extubation

Abstract Criteria to identify patients who are ready to be liberated from mechanical ventilation (MV) are imprecise, often resulting in prolonged MV or reintubation, both of which are associated with adverse outcomes. Daily protocol-driven assessment of the need for MV leads to earlier extubation bu...

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Detaylı Bibliyografya
Asıl Yazarlar:	Samuel W. Fenske, Alec Peltekian, Mengjia Kang, Nikolay S. Markov, Mengou Zhu, Kevin Grudzinski, Melissa J. Bak, Anna Pawlowski, Vishu Gupta, Yuwei Mao, Stanislav Bratchikov, Thomas Stoeger, Luke V. Rasmussen, Alok N. Choudhary, Alexander V. Misharin, Benjamin D. Singer, G. R. Scott Budinger, Richard G. Wunderink, Ankit Agrawal, Catherine A. Gao, NU SCRIPT Study Investigators
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	Nature Portfolio 2025-07-01
Seri Bilgileri:	Scientific Reports
Konular:	Machine learning Deep learning Critical care Mechanical ventilation Respiratory failure
Online Erişim:	https://doi.org/10.1038/s41598-025-12264-4
Etiketler:	Etiketle Etiket eklenmemiş, İlk siz ekleyin!

Developing and validating machine learning models to predict next-day extubation

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