Protocol for the perioperative outcome risk assessment with computer learning enhancement (Periop ORACLE) randomized study [version 2; peer review: 2 approved]

Protocol for the perioperative outcome risk assessment with computer learning enhancement (Periop ORACLE) randomized study [version 2; peer review: 2 approved]

Background: More than four million people die each year in the month following surgery, and many more experience complications such as acute kidney injury. Some of these outcomes may be prevented through early identification of at-risk patients and through intraoperative risk mitigation. Telemedicin...

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Bibliographic Details
Main Authors: Alex Kronzer, Thomas Kannampallil, Bradley Fritz, Christopher King, Troy Wildes, Arbi Ben Abdallah, Sherry McKinnon, Joanna Abraham, Yixin Chen, Bethany Tellor Pennington, Michael Avidan, Thaddeus Budelier, Arianna Montes de Oca
Format: Article
Language:English
Published: F1000 Research Ltd 2022-09-01
Series:F1000Research
Subjects:
Anesthesiology
Machine Learning
Postoperative Complications
Protocol
Surgery
eng
Online Access:https://f1000research.com/articles/11-653/v2

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