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Pediatric dermatologists versus AI bots: Evaluating the medical knowledge and diagnostic capabilities of ChatGPT.
Huang, Charles Y; Zhang, Esther; Caussade, Marie-Chantal; Brown, Trinity; Stockton Hogrogian, Griffin; Yan, Albert C.
Afiliação
  • Huang CY; Sidney Kimmel Medical College, Philadelphia, Pennsylvania, USA.
  • Zhang E; Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Caussade MC; Section of Dermatology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
  • Brown T; Section of Dermatology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
  • Stockton Hogrogian G; Section of Dermatology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
  • Yan AC; Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Pediatr Dermatol ; 2024 May 09.
Article em En | MEDLINE | ID: mdl-38721744
ABSTRACT
This study evaluates the clinical accuracy of OpenAI's ChatGPT in pediatric dermatology by comparing its responses on multiple-choice and case-based questions to those of pediatric dermatologists. ChatGPT's versions 3.5 and 4.0 were tested against questions from the American Board of Dermatology and the "Photoquiz" section of Pediatric Dermatology. Results show that human pediatric dermatology clinicians generally outperformed both ChatGPT iterations, though ChatGPT-4.0 demonstrated comparable performance in some areas. The study highlights the potential of AI tools in aiding clinicians with medical knowledge and decision-making, while also emphasizing the need for continual advancements and clinician oversight in using such technologies.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article