Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications

OBJECTIVE: To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury. DESIGN: Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010. PATIENTS: 50,318 adult patients undergoing major surgery. MEASUREMENTS...

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Vydáno v:PLoS One
Hlavní autoři: Thottakkara, Paul, Ozrazgat-Baslanti, Tezcan, Hupf, Bradley B., Rashidi, Parisa, Pardalos, Panos, Momcilovic, Petar, Bihorac, Azra
Médium: Artigo
Jazyk:Inglês
Vydáno: Public Library of Science 2016
Témata:
Research Article
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC4883761/
https://ncbi.nlm.nih.gov/pubmed/27232332
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0155705
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