Published on in Vol 27 (2025)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/64348, first published
.
Token Probabilities to Mitigate Large Language Models Overconfidence in Answering Medical Questions: Quantitative Study
Token Probabilities to Mitigate Large Language Models Overconfidence in Answering Medical Questions: Quantitative Study
Journals
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- Callens S. Effective prompt design for large language models in clinical practice. Acta Clinica Belgica 2026;81(2):118 View
- Small W, Crowley R, Pariente C, Zhang J, Eaton K, Jiang L, Oermann E, Aphinyanaphongs Y. Enhancing the prediction of hospital discharge disposition with extraction-based language model classification. npj Health Systems 2026;3(1) View
- Santarelli V, Lombardo R, Romagnoli M, Sequi M, Coppola L, Rosato E, De Cillis S, Checcucci E, Amparore D, Ragonese M, Foschi N, Spatafora P, Tema G, Nacchia A, Cicione A, Franco A, Pastore A, Al Salhi Y, Gallo G, Pagliarulo V, Rocco B, Gacci M, Fiori C, Finazzi Agro E, Sciarra A, Del Giudice F, Tubaro A, De Nunzio C. Accuracy, readability, and understandability of European Association of Urology guidelines bot for Sexual and Reproductive Health Guidelines. The Journal of Sexual Medicine 2026;23(4) View
- Zidan A, El-Sururi M, Belbase A, Saleh Y, Kalasipudi R, Al-Rawi R, Malik A, Gupta S, Perez M. Confidence-Accuracy Alignment in Cardiology Knowledge: Comparing Medical-Specific and General-Purpose Large Language Models Using ACCSAP. The American Journal of Cardiology 2026;272:132 View
- Schramm S, Le Guellec B, Topka M, Svec M, Backhaus P, Eisenkolb V, Riedel E, Beyrle M, Platzek P, Ramschütz C, Paprottka K, Renz M, Bodden J, Kirschke J, Ziegelmayer S, Busch F, Makowski M, Adams L, Bressem K, Hedderich D, Wiestler B, Kim S. Performing Best When Needed Least: Reader Experience Shapes Accuracy Gains in Large Language Model–assisted Brain MRI Differential Diagnosis. Radiology 2026;319(2) View
- Boie S, Reis F, Frey N, Grünewald E, Balzer F. Calibration of Self-Reported Confidence and Accuracy of Large Language Models in Medical Question Answering. Journal of Medical Systems 2026;50(1) View
- Carpio Salmerón M, Carazo-Casas C, Benito P, Garcia C, Alonso-Carrillo J, Carratalá B, Kyriakos G, González-Castro P. Frontier Large Language Models on the 2026 Spanish MIR Examination: A Multimodal Cross-Sectional Evaluation.. Revista Española de Educación Médica 2026;7(4) View
- Shi S, Wang C, Zhang A, Zhang K, Chen Y, Shen J, Binwal S. A Knowledge Service System for Foundation Pit Engineering Based on LoRA and RAG. Advances in Civil Engineering 2026;2026(1) View
- Arzehgar A, Varasteh Yazdi S, Ahanchian H, Eslami S. Retrieval-Augmented Language Models for Clinical Decision Support in the Classification of Inborn Errors of Immunity. Journal of Clinical Immunology 2026;46(1) View
- Tilley A, Murray B, Henry K, Zhao X, Gao Y, Blotske K, Sikora A. Navigating uncertainty matters: Evaluating large language models for drug-drug interaction identification. Journal of Managed Care & Specialty Pharmacy 2026;32(9):1076 View
- Gong M, Ma Y, Pan H, Bai H, Dai H, Chen W, Liu H, Gong K, Zeng Z, Wu H, Ouyang Z, Luo Y, Zhang B, Liu J, Ji X. Expert consensus on ethical governance of clinical applications of generative medical artificial intelligence (GMAI) (2025). JME Practical Bioethics 2026;2(3):e000136 View
- Hirosawa T, Harada Y, Kawamura R, Shimizu T. Conditional Perplexity Scoring for Large Language Model−Generated Differential Diagnoses in Case Reports: Preliminary Computational Evaluation. JMIR Formative Research 2026;10:e98819 View
Conference Proceedings
- Tahermazandarani M, Mahmood A, Islam F, Sheng Q. 2026 IEEE International Conference on Digital Health (ICDH). When Confidence Fails: Overconfidence in LLMS Under Uncertainty and Missing Clinical Information View