Explainable machine-learning predictions for the prevention of hypoxaemia during surgery

Although anaesthesiologists strive to avoid hypoxemia during surgery, reliably predicting future intraoperative hypoxemia is not currently possible. Here, we report the development and testing of a machine-learning-based system that, in real time during general anaesthesia, predicts the risk of hypo...

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Detalles Bibliográficos
Autores principales: Lundberg, Scott M., Nair, Bala, Vavilala, Monica S., Horibe, Mayumi, Eisses, Michael J., Adams, Trevor, Liston, David E., King-Wai Low, Daniel, Newman, Shu-Fang, Kim, Jerry, Lee, Su-In
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467492/
https://www.ncbi.nlm.nih.gov/pubmed/31001455
http://dx.doi.org/10.1038/s41551-018-0304-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467492/
https://www.ncbi.nlm.nih.gov/pubmed/31001455
http://dx.doi.org/10.1038/s41551-018-0304-0

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