The arrival of large language models like Open AI's ChatGPT, Microsoft's Copilot and Google's Gemini AI heralds a revolutionary era in various medical fields including the interpretation of histopathology reports. Histopathology is a foundation in diagnostic medicine which traditionally depends on the skill of a histopathologist to interpret cytology and tissue biopsies. However, a fusion of large language models (artificial intelligence) has enhanced diagnostic accuracy and lessened the workload burden on pathologists especially in human resource-constrained setups. This editorial explores the merits and demerits of integrating large language models for interpreting histopathology reports supported by evidence.
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