Using machine learning techniques to develop forecasting algorithms for postoperative complications: protocol for a retrospective study

INTRODUCTION: Mortality and morbidity following surgery are pressing public health concerns in the USA. Traditional prediction models for postoperative adverse outcomes demonstrate good discrimination at the population level, but the ability to forecast an individual patient’s trajectory in real tim...

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Detalles Bibliográficos
Autores principales: Fritz, Bradley A, Chen, Yixin, Murray-Torres, Teresa M, Gregory, Stephen, Ben Abdallah, Arbi, Kronzer, Alex, McKinnon, Sherry Lynn, Budelier, Thaddeus, Helsten, Daniel L, Wildes, Troy S, Sharma, Anshuman, Avidan, Michael Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2018
Materias:
Anaesthesia
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898287/
https://www.ncbi.nlm.nih.gov/pubmed/29643160
http://dx.doi.org/10.1136/bmjopen-2017-020124

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898287/
https://www.ncbi.nlm.nih.gov/pubmed/29643160
http://dx.doi.org/10.1136/bmjopen-2017-020124

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