Measured Performance and Healthcare Professional Perception of Large Language Models Used as Clinical Decision Support Systems: A Scoping Review - Archive ouverte HAL
Chapitre D'ouvrage Année : 2024

Measured Performance and Healthcare Professional Perception of Large Language Models Used as Clinical Decision Support Systems: A Scoping Review

Résumé

The healthcare sector confronts challenges from overloaded tumor board meetings, reduced discussion durations, and care quality concerns, necessitating innovative solutions. Integrating Clinical Decision Support Systems (CDSSs) has a potential in supporting clinicians to reduce the cancer burden, but CDSSs remain poorly used in clinical practice. The emergence of OpenAI’s ChatGPT in 2022 has prompted the evaluation of Large Language Models (LLMs) as potential CDSSs for diagnosis and therapeutic management. We conducted a scoping review to evaluate the utility of LLMs like ChatGPT as CDSSs in several medical specialties, particularly in oncology, and compared users’ perception of LLMs with the actually measured performance of these systems.

Dates et versions

hal-04699249 , version 1 (16-09-2024)

Identifiants

Citer

Solène Delourme, Akram Redjdal, Jacques Bouaud, Brigitte Seroussi. Measured Performance and Healthcare Professional Perception of Large Language Models Used as Clinical Decision Support Systems: A Scoping Review. Digital Health and Informatics Innovations for Sustainable Health Care Systems, IOS Press, 2024, Studies in Health Technology and Informatics, ⟨10.3233/SHTI240543⟩. ⟨hal-04699249⟩
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