Machine learning of physiological waveforms and electronic health record data to predict, diagnose and treat haemodynamic instability in surgical patients: protocol for a retrospective study

INTRODUCTION: About 42 million surgeries are performed annually in the USA. While the postoperative mortality is less than 2%, 12% of all patients in the high-risk surgery group account for 80% of postoperative deaths. New onset of haemodynamic instability is common in surgical patients and its dela...

Descripción completa

Detalles Bibliográficos
Autores principales: Cannesson, Maxime, Hofer, Ira, Rinehart, Joseph, Lee, Christine, Subramaniam, Kathirvel, Baldi, Pierre, Dubrawski, Artur, Pinsky, Michael R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Anaesthesia
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003391/
https://www.ncbi.nlm.nih.gov/pubmed/31796483
http://dx.doi.org/10.1136/bmjopen-2019-031988

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003391/
https://www.ncbi.nlm.nih.gov/pubmed/31796483
http://dx.doi.org/10.1136/bmjopen-2019-031988

Ejemplares similares