TY - JOUR
T1 - Ethical guidance for reporting and evaluating claims of AI outperforming human doctors
AU - Drogt, Jojanneke
AU - Milota, Megan
AU - van den Brink, Anne
AU - Jongsma, Karin
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/10/2
Y1 - 2024/10/2
N2 - Claims of AI outperforming medical practitioners are under scrutiny, as the evidence supporting many of these claims is not convincing or transparently reported. These claims often lack specificity, contextualization, and empirical grounding. In this comment, we offer constructive ethical guidance that can benefit authors, journal editors, and peer reviewers when reporting and evaluating findings in studies comparing AI to physician performance. The guidance provided here forms an essential addition to current reporting guidelines for healthcare studies using machine learning.
AB - Claims of AI outperforming medical practitioners are under scrutiny, as the evidence supporting many of these claims is not convincing or transparently reported. These claims often lack specificity, contextualization, and empirical grounding. In this comment, we offer constructive ethical guidance that can benefit authors, journal editors, and peer reviewers when reporting and evaluating findings in studies comparing AI to physician performance. The guidance provided here forms an essential addition to current reporting guidelines for healthcare studies using machine learning.
UR - http://www.scopus.com/inward/record.url?scp=85205953010&partnerID=8YFLogxK
U2 - 10.1038/s41746-024-01255-w
DO - 10.1038/s41746-024-01255-w
M3 - Comment/Letter to the editor
AN - SCOPUS:85205953010
SN - 2398-6352
VL - 7
JO - NPJ DIGITAL MEDICINE
JF - NPJ DIGITAL MEDICINE
IS - 1
M1 - 271
ER -