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Reactive Artificial Intelligence Using Big Data in the Era of Precision Medicine

Reactive Artificial Intelligence Using Big Data in the Era of Precision Medicine Letters (Hall); Wolff Center, University of Pittsburgh Medical Center, Pittsburgh, The practical and effective applications begin with data ac- Pennsylvania (Hall). quisition, ie, large data sets that will enable advanced AI and Corresponding Author: Myrick C. Shinall Jr, MD, PhD, Vanderbilt University machine learning models. We believe today's AI technology Medical Center, 1161 21st Ave S, Room D5203 MCN, Nashville, TN 37232 should be used to actively generate hypotheses to eventually (ricky.shinall@vumc.org). allow us to explore the role of limited AI for better health care Published Online: April 22, 2020. doi:10.1001/jamasurg.2020.0431 solutions. Conflict of Interest Disclosures: Dr Shinall reported grants from National Cancer Institute during the conduct of the study. Dr Shireman reported grants from National Institutes of Health and grants from Veterans Health Ankita Kar, MDS Administration during the conduct of the study. No other disclosures Anand Subash, MS, DNB were reported. Vishal U. S. Rao, MS 1. Shinall MC Jr, Arya S, Youk A, et al. Association of preoperative patient frailty and operative stress with postoperative mortality. JAMA Surg. 2019;155(1): Author Affiliations: Department of Head and Neck Oncology, Health Care e194620. Global Cancer Center, Bangalore, India. 2. Arya S, Varley P, Youk A, et al. Recalibration and http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JAMA Surgery American Medical Association

Reactive Artificial Intelligence Using Big Data in the Era of Precision Medicine

JAMA Surgery , Volume 155 (7) – Jul 6, 2020

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Publisher
American Medical Association
Copyright
Copyright 2020 American Medical Association. All Rights Reserved.
ISSN
2168-6254
eISSN
2168-6262
DOI
10.1001/jamasurg.2020.0839
Publisher site
See Article on Publisher Site

Abstract

Letters (Hall); Wolff Center, University of Pittsburgh Medical Center, Pittsburgh, The practical and effective applications begin with data ac- Pennsylvania (Hall). quisition, ie, large data sets that will enable advanced AI and Corresponding Author: Myrick C. Shinall Jr, MD, PhD, Vanderbilt University machine learning models. We believe today's AI technology Medical Center, 1161 21st Ave S, Room D5203 MCN, Nashville, TN 37232 should be used to actively generate hypotheses to eventually (ricky.shinall@vumc.org). allow us to explore the role of limited AI for better health care Published Online: April 22, 2020. doi:10.1001/jamasurg.2020.0431 solutions. Conflict of Interest Disclosures: Dr Shinall reported grants from National Cancer Institute during the conduct of the study. Dr Shireman reported grants from National Institutes of Health and grants from Veterans Health Ankita Kar, MDS Administration during the conduct of the study. No other disclosures Anand Subash, MS, DNB were reported. Vishal U. S. Rao, MS 1. Shinall MC Jr, Arya S, Youk A, et al. Association of preoperative patient frailty and operative stress with postoperative mortality. JAMA Surg. 2019;155(1): Author Affiliations: Department of Head and Neck Oncology, Health Care e194620. Global Cancer Center, Bangalore, India. 2. Arya S, Varley P, Youk A, et al. Recalibration and

Journal

JAMA SurgeryAmerican Medical Association

Published: Jul 6, 2020

References