{
  "id": 13211,
  "url": "https://www.jmir.org/2026/1/e92931",
  "title": "Diagnostic Performance of Large Language Models for Orthopedic-Related Rare Diseases and Their Impact on Physicians’ Diagnostic Accuracy: 2-Stage Comparative Evaluation Study Based on the Chinese Rare Disease Catalog",
  "summary": "Background: Orthopedic-related rare diseases are difficult to diagnose because of their low prevalence, heterogeneous phenotypes, and fragmented knowledge. Large language models (LLMs) can serve as dynamic knowledge-support tools, but their diagnostic performance and effect on physicians’ decision-making remain unclear. Objective: This study aims to compare the diagnostic performance of advanced LLMs for orthopedic-related rare diseases and to evaluate the effect of a 2-stage LLM-assisted diagno",
  "authors": "Tusheng Li, Ziqian Ma, Baodong Wang, Ning Fan, Aobo Wang, Lei Zang",
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": "china",
  "published_at": "2026-07-24T19:00:35.000Z",
  "fetched_at": "2026-07-25T05:10:48.796Z",
  "source_slug": "x-jmir-journal-of-medical-internet-researc",
  "source_name": "JMIR (Journal of Medical Internet Research)",
  "source_homepage": "https://www.jmir.org",
  "ethics_ai_record_url": "https://ethics.ai/record/13211",
  "original_url": "https://www.jmir.org/2026/1/e92931",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}