Large Language Models' Performances regarding logical observation identifiers names and codes mapping in laboratory medicine: A comparative analysis of ChatGPT-4.0, Gemini, and Perplexity.
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| Title: | Large Language Models' Performances regarding logical observation identifiers names and codes mapping in laboratory medicine: A comparative analysis of ChatGPT-4.0, Gemini, and Perplexity. |
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| Authors: | Yu S; Department of Laboratory Medicine, Haeundae Paik Hospital, Inje University College of Medicine, Busan, South Korea., Cho EJ; Department of Laboratory Medicine, Hallym University Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, South Korea. Electronic address: ejlovi@naver.com., Kim S; Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea., Park K; Department of Laboratory Medicine, Sanggye Paik Hospital, College of Medicine, Inje University, Seoul, South Korea., Kim MS; Department of Laboratory Medicine, Soonchunhyang University Cheonan Hospital, Soonchunhyang University College of Medicine, Cheonan, South Korea., Oh Y; Department of Laboratory Medicine, Green Cross Laboratories, Yongin, South Korea., Ryu H; Department of Laboratory Medicine, Seegene Medical Foundation, Seoul, South Korea. |
| Source: | International journal of medical informatics [Int J Med Inform] 2026 Apr 01; Vol. 209, pp. 106270. Date of Electronic Publication: 2026 Jan 06. |
| Publication Type: | Journal Article; Comparative Study |
| Journal Info: | Publisher: Elsevier Science Ireland Ltd Country of Publication: Ireland NLM ID: 9711057 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-8243 (Electronic) Linking ISSN: 13865056 NLM ISO Abbreviation: Int J Med Inform Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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