{
  "id": 2426,
  "url": "https://www.jmir.org/2026/1/e90692",
  "title": "Fine-Tuning, Retrieval-Augmented Generation, and Hybrid Large Language Models for Postoperative Decision Support: Comparative Analysis",
  "summary": "Background: Large language models (LLMs) show growing potential for decision support. However, integrating domain-specific medical knowledge while maintaining accuracy, safety, and interpretability remains challenging for postoperative discharge instructions and patient education. Fine-tuning, retrieval-augmented generation (RAG), and hybrid fine-tuning+RAG approaches are prominent strategies for knowledge integration, but their comparative performance in postoperative care has not been systemat",
  "authors": "Srinivasagam Prabha, Bernardo Gabriele Collaco, Cesar Abraham Gomez-Cabello, Syed Ali Haider, Ariana Genovese, Zhihui Fang, Nadia Wood, Sanjay Bagaria, Cui Tao, Antonio Jorge Forte",
  "category": "research",
  "topics": "safety-alignment,healthcare,children-education",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-14T16:00:14.000Z",
  "fetched_at": "2026-07-14T16:11:46.979Z",
  "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/2426",
  "original_url": "https://www.jmir.org/2026/1/e90692",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}