Use of Artificial Intelligence to Represent Emergent Systems and Augment Surgical Decision-making
Author:
Affiliation:
1. Department of Surgery, University of Florida Health, Gainesville
2. Department of Medicine, University of Florida Health, Gainesville
Publisher
American Medical Association (AMA)
Subject
Surgery
Link
https://jamanetwork.com/journals/jamasurgery/articlepdf/2736338/jamasurgery_loftus_2019_vp_190005.pdf
Reference7 articles.
1. The regulation of ant colony foraging activity without spatial information.;Prabhakar;PLoS Comput Biol,2012
2. Loss of “complexity” and aging: potential applications of fractals and chaos theory to senescence.;Lipsitz;JAMA,1992
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. Comparing clinical judgment with the MySurgeryRisk algorithm for preoperative risk assessment: a pilot usability study.;Brennan;Surgery,2019
5. The Third International Consensus definitions for sepsis and septic shock (sepsis-3).;Singer;JAMA,2016
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