Evaluating Multiple Input Strategies of Large Language Models for Gallbladder Polyps on Ultrasound: Comparative Study.

ABSTRACT:

Background

Gallbladder polyps have a high prevalence and are predominantly benign lesions, often detected via ultrasound. They impose diagnostic burdens on radiologists while generating substantial patient demand for report interpretation. Benign polyps include nonneoplastic polyps without malignant potential and premalignant adenomas that require cholecystectomy. Current guidelines recommending surgery for polyps ≥1.0 cm may lead to unnecessary interventions. Advanced multimodal large language models (LLMs) such as ChatGPT-4o (OpenAI) and Claude 3.5 Sonnet (Anthropic PBC) demonstrate emerging capabilities in medical image analysis. Implementing LLMs in gallbladder polyp ultrasound evaluation can potentially alleviate radiologists' workload, provide patient-accessible consultation

SUBMITTER: Jiang L 

PROVIDER: S-EPMC12777648 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature