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research article

Gender Bias in AI's Perception of Cardiovascular Risk

Achtari, Margaux
•
Salihu, Adil
•
Muller, Olivier
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2024
Journal of Medical Internet Research

The study investigated gender bias in GPT-4's assessment of coronary artery disease risk by presenting identical clinical vignettes of men and women with and without psychiatric comorbidities. Results suggest that psychiatric conditions may influence GPT-4's coronary artery disease risk assessment among men and women.

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Type
research article
DOI
10.2196/54242
Scopus ID

2-s2.0-85207222605

PubMed ID

39437384

Author(s)
Achtari, Margaux

Centre Universitaire de Médecine Générale et Santé Publique, Lausanne

Salihu, Adil

Centre Hospitalier Universitaire Vaudois

Muller, Olivier

Centre Hospitalier Universitaire Vaudois

Abbé, Emmanuel  

École Polytechnique Fédérale de Lausanne

Clair, Carole

Centre Universitaire de Médecine Générale et Santé Publique, Lausanne

Schwarz, Joëlle

Centre Universitaire de Médecine Générale et Santé Publique, Lausanne

Fournier, Stephane

Centre Hospitalier Universitaire Vaudois

Date Issued

2024

Published in
Journal of Medical Internet Research
Volume

26

Article Number

e54242

Subjects

AI

•

artery

•

artificial intelligence

•

CAD

•

cardiovascular

•

chatbot: health care

•

coronary

•

coronary artery disease

•

gender

•

gender bias

•

gender equity

•

men: women

•

risk

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
MDS1  
FunderFunding(s)Grant NumberGrant URL

Edwards Lifesciences and Abbott

Available on Infoscience
January 25, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/243945
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