Generative artificial intelligence (AI) for reporting the performance of laboratory biomarkers: not ready for prime time
Author:
Affiliation:
1. Section of Clinical Biochemistry , University of Verona , Verona , Italy
Publisher
Walter de Gruyter GmbH
Link
https://www.degruyter.com/document/doi/10.1515/cclm-2024-0857/pdf
Reference8 articles.
1. Carobene, A, Cabitza, F, Bernardini, S, Gopalan, R, Lennerz, JK, Weir, C, et al.. Where is laboratory medicine headed in the next decade? Partnership model for efficient integration and adoption of artificial intelligence into medical laboratories. Clin Chem Lab Med 2023;61:1359. https://doi.org/10.1515/cclm-2022-1030.
2. Plebani, M. ChatGPT: Angel or Demond? Critical thinking is still needed. Clin Chem Lab Med 2023;61:1131–2. https://doi.org/10.1515/cclm-2023-0387.
3. Cadamuro, J, Cabitza, F, Debeljak, Z, De Bruyne, S, Frans, G, Perez, SM, et al.. Potentials and pitfalls of ChatGPT and natural-language artificial intelligence models for the understanding of laboratory medicine test results. An assessment by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Artificial Intelligence (WG-AI). Clin Chem Lab Med 2023;61:1158–66. https://doi.org/10.1515/cclm-2023-0355.
4. Meyer, A, Soleman, A, Riese, J, Streichert, T. Comparison of ChatGPT, Gemini, and Le Chat with physician interpretations of medical laboratory questions from an online health forum. Clin Chem Lab Med 2024 May 29. https://doi.org/10.1515/cclm-2024-0246. [Epub ahead of print].
5. Diamandis, EP. Chatbot GPT can be grossly inaccurate. Clin Chem Lab Med 2023;62:e25. https://doi.org/10.1515/cclm-2023-0765.
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