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

Comparative Evaluation of Large Language Models in Answering Patient Questions Following Periodontal and Peri-Implant Examination: An Expert-Based Study.

G Gemini demonstrated superior clinical precision and safety, whereas Claude provided more comprehensive and readable explanations, which support the integration of LLMs as pragmatic, high-ecological-validity complementary tools for patient education, while emphasizing the persistent necessity for professional clinical...

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

Vision and Language Models for Classifying Maxillary Sinus Disease on Cone-Beam Computed Tomography: A Transparent Multimodal Benchmark

Background: Cone-beam computed tomography (CBCT) frequently captures the maxillary sinuses incidentally, and reliable automated detection of sinus abnormality is clinically relevant. Unlike most vision-language benchmarks in medical imaging, which pair images with pre-existing, human-authored clinical reports, findings...

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...

Vision-Language Model as a ‘Zero-Shot’ Assistant for Evaluating Condylar Osseous Changes in Cone-beam Computed Tomography

VLMs, particularly Gemini-3, exhibit zero-shot capabilities in identifying condylar changes and generating high-quality diagnostic reports, and demonstrate potential as preliminary, training-free screening aids in oral maxillofacial radiology.

Image-Based Diagnosis of Oral Lesions: Performance of a Vision-Language Model versus Human Clinicians.

OBJECTIVE To evaluate the real-world diagnostic performance of a multimodal large language model (LLM) for image-based assessment of oral mucosal lesions compared with clinicians of varying expertise. STUDY DESIGN Prospective international multicenter diagnostic accuracy study. SETTING Twenty university and tertiar...