Multimodal large language models for oral lesion diagnosis: a systematic review of diagnostic performance and clinical utility

Abstract

Diagnosing oral lesions from benign conditions to oral cancer remains challenging due to overlapping visual features and reliance on histopathology. Large language models (LLMs) can integrate textual and visual cues, but their diagnostic accuracy and clinical utility in real decision-making contexts remain uncertain. To systematically evaluate the diagnostic performance, clinical usefulness, and limitations of LLMs in identifying oral lesions.