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Authors
Nguyen, Khoa
Wilson, Debbie L.
Diiulio, Julie
Hall, Bradley
Militello, Laura
Gellad, Walid F.
Harle, Christopher A.
Lewis, Motomori
Schmidt, Siegfried
Rosenberg, Eric I.
Nelson, Danielle
He, Xing
Wu, Yonghui
Bian, Jiang
Staras, Stephanie A. S.
Gordon, Adam J.
Cochran, Jerry
Kuza, Courtney
Yang, Seonkyeong
Lo-Ciganic, Weihsuan
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Article History
Received: 15 July 2024
Accepted: 8 September 2024
First Online: 18 October 2024
Declarations
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: The study was approved by the University of Florida Institutional Review Board (IRB202002225). Study participants agreed to a waiver of documentation of consent prior to participating.
: This manuscript does not contain any individual person’s data in any form (i.e., individual details, images, or videos), thus consent for publication from an individual is not warranted.
: Drs. Wilson and Lo-Ciganic have received grant funding from Merck Sharp & Dohme and Bristol Myers Squibb unrelated to this work. Drs. Lo-Ciganic and Gellad are named as inventors in a preliminary patent filing from the University of Florida for use of a machine learning algorithm for opioid risk prediction.
