Your browser doesn't support javascript.
loading
Multi role ChatGPT framework for transforming medical data analysis.
Chen, Haoran; Zhang, Shengxiao; Zhang, Lizhong; Geng, Jie; Lu, Jinqi; Hou, Chuandong; He, Peifeng; Lu, Xuechun.
Afiliación
  • Chen H; School of Management, Shanxi Medical University, Taiyuan, 030000, China.
  • Zhang S; Department of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing,
  • Zhang L; Department of Rheumatology and Immunology, The Second Hospital of Shanxi Medical University, Taiyuan, China.
  • Geng J; Key Laboratory of Coal Environmental Pathogenicity and Prevention at Shanxi Medical University, Ministry of Education, Taiyuan, Shanxi, China.
  • Lu J; SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine, Shanxi Medical University, Taiyuan, China.
  • Hou C; Basic Medicine College, Shanxi Medical University, Taiyuan, 030000, China.
  • He P; Basic Medicine College, Shanxi Medical University, Taiyuan, 030000, China.
  • Lu X; Department of Computer Science, Boston University, 665 Commonwealth Avenue, Boston, MA, 02215, USA.
Sci Rep ; 14(1): 13930, 2024 06 17.
Article en En | MEDLINE | ID: mdl-38886470
ABSTRACT
The application of ChatGPTin the medical field has sparked debate regarding its accuracy. To address this issue, we present a Multi-Role ChatGPT Framework (MRCF), designed to improve ChatGPT's performance in medical data analysis by optimizing prompt words, integrating real-world data, and implementing quality control protocols. Compared to the singular ChatGPT model, MRCF significantly outperforms traditional manual analysis in interpreting medical data, exhibiting fewer random errors, higher accuracy, and better identification of incorrect information. Notably, MRCF is over 600 times more time-efficient than conventional manual annotation methods and costs only one-tenth as much. Leveraging MRCF, we have established two user-friendly databases for efficient and straightforward drug repositioning analysis. This research not only enhances the accuracy and efficiency of ChatGPT in medical data science applications but also offers valuable insights for data analysis models across various professional domains.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Análisis de Datos Límite: Humans Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Análisis de Datos Límite: Humans Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido