Multi-Agent AI for Chest Radiography: A Sequential Segmentation and LLM-Driven Consultative Tool for Medical Training

Abstract excerpt

<h4>Background</h4> Traditional diagnostic models lack explainability, while multimodal language models prone to hallucination remain unsafe for medical education. An interactive, risk-free artificial intelligence framework is required to serve as a reliable clinical mentor for radiology trainees. <h4>Methods</h4> We propose a multi-agent architecture decoupling deterministic image analysis from generative consu...

Topics

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• Artificial Intelligence
• Decision Support Systems, Clinical
• Diagnosis, Differential
• Electronic Health Records
• Genetic Variation
• Genetics, Medical
• Phenotype
• Rare Diseases

Identifiers and source

Literature Corpus work

843872f9-4c94-52c8-811f-feb4d545c89a

DOI

10.64898/2026.05.29.26354432