Work

Gender Bias in AI's Perception of Cardiovascular Risk

Year: 2024

Type: article

Abstract: 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.

Source: Journal of Medical Internet Research

DOI: 10.2196/54242

Authors: Margaux Achtari, Adil Salihu, Olivier Muller, Emmanuel Abbé, Carole Clair, Joëlle Schwarz, Stephane Fournier

Institutions: Centre universitaire de médecine générale et santé publique, Lausanne, University of Lausanne, Centre Hospitalier Universitaire Vaudois, École Polytechnique Fédérale de Lausanne

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,309

OpenAlex ID: W4402421102

FWCI: 0.953

Cites: 13

Cited by: 12

Related to: 10