Advantages and Inconveniences of a Multi-Agent Large Language Model System to Mitigate Cognitive Biases in Diagnostic Challenges

Authors

Divà Beltramin (ORCID: https://orcid.org/0000-0001-8498-6150)
Cédric Bousquet (ORCID: https://orcid.org/0000-0001-9775-2476)

Institutions

Inserm (FR)
Sorbonne Université (FR)
Université Sorbonne Paris Nord (FR)
Sorbonne Paris Cité (FR)
Hospices Civils de Lyon (FR)
Institut de Médecine et d'Epidémiologie Africaines (FR)
Laban/Bartenieff Institute of Movement Studies (US)
Centre Hospitalier Universitaire de Saint-Étienne (FR)
Département d'Informatique (FR)
Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé

Publication Details

Journal: Journal of Medical Internet Research
Published: 2024-12-11
DOI: https://doi.org/10.2196/69742
Citations: 1
Primary Topic: Machine Learning in Healthcare
Type: article
Field-Weighted Citation Impact: 0.35

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article

Advantages and Inconveniences of a Multi-Agent Large Language Model System to Mitigate Cognitive Biases in Diagnostic Challenges

Divà Beltramin, Cédric Bousquet

Dec 11, 2024

1 citations

Journal of Medical Internet Research

Machine Learning in Healthcare

0.35

article

Advantages and Inconveniences of a Multi-Agent Large Language Model System to Mitigate Cognitive Biases in Diagnostic Challenges

Divà Beltramin, Cédric Bousquet

December 11, 2024article en

1 citations

Abstract

No abstract available for this paper.

Journal of Medical Internet ResearchVol. 27

Inserm (FR), Sorbonne Université (FR), Université Sorbonne Paris Nord (FR), Sorbonne Paris Cité (FR), Hospices Civils de Lyon (FR), Institut de Médecine et d'Epidémiologie Africaines (FR), Laban/Bartenieff Institute of Movement Studies (US), Centre Hospitalier Universitaire de Saint-Étienne (FR), Département d'Informatique (FR), Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé

Quality Education

Openalex Percentile: Top 31%

Machine Learning in Healthcare

0.35

DOI Open Access PDF OpenAlex

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