Bias and ethical considerations in machine learning and the automation of perioperative risk assessment

• Type of Material: Article
• Authors: Vikas N. O'Reilly-Shah, Emory University; Joel B Zivot, Emory University; Katherine R. Gentry, University of Washington; Andrew M. Walters, University of Washington
• Language: English
• Date: 2020-12-01
• Publisher: ELSEVIER SCI LTD
• Publication Version: Final Published Version
• Copyright Statement: © 2020 British Journal of Anaesthesia. Published by Elsevier Ltd.
• Final Published Version (URL): http://dx.doi.org/10.1016/j.bja.2020.07.040
• Title of Journal or Parent Work: BRITISH JOURNAL OF ANAESTHESIA
• Volume: 125
• Issue: 6
• Start Page: 843
• End Page: 846
• Grant/Funding Information: United States National Institutes of Health NIH grants R01GM114290 (National Institute of General Medical Sciences), R01AG121647 (National Institute on Aging), and U24NS113800 (National Institute of Neurological Disorders and Stroke) (PJT).
• Keywords: healthcare inequality; artificial intelligence; Anesthesiology; racial; Science & Technology; machine learning; perioperative medicine; CALCULATOR; gender bias; bias; HEALTH; risk prediction; Life Sciences & Biomedicine
• Research Categories: Health Sciences, Health Care Management; Health Sciences, Medicine and Surgery