Artificial intelligence assisted diagnosis of chronic lymphocytic leukemia in a historic pediatric case using large language models.

This article discusses the use of large language models (LLMs) in diagnosing a historic case of pediatric leukemia. The authors selected a 19th-century case report of a child with unclassified leukemia and used four LLMs to analyze the clinical information and provide a diagnosis. Three out of the four LLMs diagnosed chronic lymphocytic leukemia (CLL), while one made an incorrect diagnosis of chronic myeloid leukemia (CML). The article highlights the limitations and potential biases of LLMs in diagnosing historical medical cases and emphasizes the importance of clinician expertise in making accurate diagnoses. [Extracted from the article]