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Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73233, first published .
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Enhancing the Accuracy of Human Phenotype Ontology Identification: Comparative Evaluation of Multimodal Large Language Models

Enhancing the Accuracy of Human Phenotype Ontology Identification: Comparative Evaluation of Multimodal Large Language Models

Journals

  1. Ho M, Zitnik M, Azachi R, Basu S, Rajpurkar P, Sidlow R. Unifying the odyssey: artificial intelligence for rare disease diagnosis and therapy. Health and Technology 2026;16(3):621 View
  2. Zhong W, Yan H, Liu Y, Liu Y, Yang K, Gao H, Yao Z, Hao W, Yan Y, Yin C. Adaptive Fast-Slow Large Language Model Framework for Multidimensional Classification of Prenatal Ultrasound Reports: Comparative Study. Journal of Medical Internet Research 2026;28:e91399 View
  3. Yang J, Yang S, Shao Z, Chen T, Shen H, Zhou P, Xia B, Lei X, Wang L, Xue D, Zheng S, Yu Y, Zhang Z. Large language models in emergency and critical care medicine: a comprehensive review of applications, challenges, and future directions. Burns & Trauma 2026;14 View
  4. Paoli D, Lanza M, Banchelli F, Boarini M, Borghi S, Sangiorgi L, Mordenti M. Opportunities and challenges in automated coding of electronic health records: a pilot study for rare disease registries. Frontiers in Digital Health 2026;8 View

Conference Proceedings

  1. Gujjula D, Vairachilai S, Velagapudi S. 2026 2nd International Conference on Intelligent Systems and Computational Networks (ICISCN). Semantic Consistency Analysis of Large Language Models for Rare Disease Diagnosis Using Clinical Ontologies View