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Revolutionary Potential of ChatGPT in Constructing Intelligent Clinical Decision Support Systems.
Liao, Zhiqiang; Wang, Jian; Shi, Zhuozheng; Lu, Lintao; Tabata, Hitoshi.
Afiliación
  • Liao Z; Department of Electrical Engineering and Information Systems, Graduate School of Engineering, The University of Tokyo, Tokyo, 113-8656, Japan. liao@bioxide.t.u-tokyo.ac.jp.
  • Wang J; Department of Orthopaedics, Qilu Hospital of Shandong University, Jinan, 250012, People's Republic of China.
  • Shi Z; Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo, 113-8656, Japan.
  • Lu L; Department of Orthopaedics, Qilu Hospital of Shandong University, Jinan, 250012, People's Republic of China. lulintao@mail.sdu.edu.cn.
  • Tabata H; Department of Orthopaedics, Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, 253000, People's Republic of China. lulintao@mail.sdu.edu.cn.
Ann Biomed Eng ; 52(2): 125-129, 2024 Feb.
Article en En | MEDLINE | ID: mdl-37332008
Recently, Chatbot Generative Pre-trained Transformer (ChatGPT) is recognized as a promising clinical decision support system (CDSS) in the medical field owing to its advanced text analysis capabilities and interactive design. However, ChatGPT primarily focuses on learning text semantics rather than learning complex data structures and conducting real-time data analysis, which typically necessitate the development of intelligent CDSS employing specialized machine learning algorithms. Although ChatGPT cannot directly execute specific algorithms, it aids in algorithm design for intelligent CDSS at the textual level. In this study, besides discussing the types of CDSS and their relationship with ChatGPT, we mainly investigate the benefits and drawbacks of employing ChatGPT as an auxiliary design tool for intelligent CDSS. Our findings indicate that by collaborating with human expertise, ChatGPT has the potential to revolutionize the development of robust and effective intelligent CDSS.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Sistemas de Apoyo a Decisiones Clínicas Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Ann Biomed Eng Año: 2024 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Sistemas de Apoyo a Decisiones Clínicas Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Ann Biomed Eng Año: 2024 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Estados Unidos