Added Value of Intraoperative Data for Predicting Postoperative Complications: The MySurgeryRisk PostOp Extension-Reference-Cited by-同舟云学术

Added Value of Intraoperative Data for Predicting Postoperative Complications: The MySurgeryRisk PostOp Extension

Published:2020-10 Issue: Volume:254 Page:350-363
ISSN:0022-4804
Container-title:Journal of Surgical Research
language:en
Short-container-title:Journal of Surgical Research

Author:

Datta Shounak^ORCID,Loftus Tyler J.,Ruppert Matthew M.,Giordano Chris^ORCID,Upchurch Gilbert R.,Rashidi Parisa,Ozrazgat-Baslanti Tezcan,Bihorac Azra^ORCID

Funder

University of Florida

National Institute of General Medical Sciences

National Center for Advancing Translational Sciences

Publisher

Elsevier BV

Subject

Surgery

Reference21 articles.

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3. Surgical risk is not linear: derivation and validation of a novel, user-friendly, and machine-learning-based predictive optimal trees in emergency surgery risk (POTTER) calculator;Bertsimas;Ann Surg,2018

4. MySurgeryRisk: development and validation of a machine-learning risk algorithm for major complications and death after surgery;Bihorac;Ann Surg,2018

5. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation;Charlson;J Chronic Dis,1987

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