Development and Verification of a Digital Twin Patient Model to Predict Specific Treatment Response During the First 24 Hours of Sepsis

To develop and verify a digital twin model of critically ill patient using the causal artificial intelligence approach to predict the response to specific treatment during the first 24 hours of sepsis. DESIGN: Directed acyclic graphs were used to define explicitly the causal relationship among organ...

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Detalles Bibliográficos
Autores principales: Lal, Amos, Li, Guangxi, Cubro, Edin, Chalmers, Sarah, Li, Heyi, Herasevich, Vitaly, Dong, Yue, Pickering, Brian W., Kilickaya, Oguz, Gajic, Ognjen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2020
Materias:
Original Clinical Report
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671877/
https://www.ncbi.nlm.nih.gov/pubmed/33225302
http://dx.doi.org/10.1097/CCE.0000000000000249

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671877/
https://www.ncbi.nlm.nih.gov/pubmed/33225302
http://dx.doi.org/10.1097/CCE.0000000000000249

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