This episode examines the rapidly growing field of using Large Language Models (LLMs) for automatic disease diagnosis in clinical practice. The review comprehensively maps the existing literature, clarifying which diseases and clinical data types have been addressed, the specific LLM techniques employed (such as prompting, fine-tuning, and Retrieval-Augmented Generation or RAG), and the evaluation methods used to assess performance.

Zhou, S., Xu, Z., Zhang, M. et al. Large language models for disease diagnosis: a scoping review. npj Artif. Intell. 1, 9 (2025). https://doi.org/10.1038/s44387-025-00011-z

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