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Measured Performance and Healthcare Professional Perception of Large Language Models Used as Clinical Decision Support Systems: A Scoping Review.
Delourme, Solène; Redjdal, Akram; Bouaud, Jacques; Seroussi, Brigitte.
Afiliación
  • Delourme S; Sorbonne Université, Université Sorbonne Paris Nord, INSERM, Laboratoire d'Informatique Médicale et d'Ingénierie des connaissances en e-Santé, LIMICS, Paris, France.
  • Redjdal A; Epita, Paris, France.
  • Bouaud J; Sorbonne Université, Université Sorbonne Paris Nord, INSERM, Laboratoire d'Informatique Médicale et d'Ingénierie des connaissances en e-Santé, LIMICS, Paris, France.
  • Seroussi B; Sorbonne Université, Université Sorbonne Paris Nord, INSERM, Laboratoire d'Informatique Médicale et d'Ingénierie des connaissances en e-Santé, LIMICS, Paris, France.
Stud Health Technol Inform ; 316: 841-845, 2024 Aug 22.
Article en En | MEDLINE | ID: mdl-39176924
ABSTRACT
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Sistemas de Apoyo a Decisiones Clínicas Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2024 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Países Bajos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Sistemas de Apoyo a Decisiones Clínicas Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2024 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Países Bajos