Evaluation of a cornea-specialized large language model for diagnostic and management accuracy in complex corneal cases

Development and performance of a specialized large language model for restorative treatment planning.

STATEMENT OF PROBLEM Although general-purpose large language models (LLMs) have shown some promise in supporting dental treatment planning, their performance remains suboptimal. This limitation underscores the need for specialized models tailored to restorative dentistry. PURPOSE The purpose of this study was to deve...

Evaluation of Large Language Model-Generated Recommendations in Glaucoma Surgical Decision-Making.

LLM-based chatbots can provide acceptable surgical guidance for straightforward primary surgical cases, but their utility is limited in high-risk or complex clinical settings, and their rationale quality was significantly lower in complex scenarios than in primary ones.

Large language models for ophthalmic examination understanding: from information extraction to clinical decision support

Publicly available LLMs and MLLMs are evolving from report-parsing tools toward broader ophthalmic clinical assistants, but their use should follow a task-layered validation framework in which verification and human oversight increase with the clinical consequences of error.

Expert-Guided Visual Correction for Characterizing Diagnostic Performance and Error Patterns of Multimodal Large Language Models Using Periodontal In-Service Examination Images

The expert-guided visual correction framework introduced here provides a generalizable, mechanism-based approach to benchmarking multimodal AI diagnostic performance that extends beyond periodontics to other visually driven diagnostic domains in medicine.

Diagnostic Accuracy of Multimodal Large Language Models (LLMs) for Detecting Tuberous Breast Deformity from Standardized Photographs: A Descriptive in Silico Study.

Evaluation of LLMs for Automated Dental-to-Medical Consult Letter Generation: Comparative Study

This preliminary study suggests the potential of Gemini-2.5-Pro for automated consult letter generation, though the low test-set inter-rater reliability highlights the subjective complexity of clinical text.