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This paper is in the following e-collection/theme issue:

Digital Health Reviews (1851) Development and Evaluation of Research Methods, Instruments and Tools (835) Artificial Intelligence (2404) Generative Language Models Including ChatGPT (851) Applications of AI (363) Foundation Models and Their Applications in AI (61) Responsible Health AI (92)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/80557, first published .
Improving Large Language Model Applications in the Medical and Nursing Domains With Retrieval-Augmented Generation: Scoping Review

Improving Large Language Model Applications in the Medical and Nursing Domains With Retrieval-Augmented Generation: Scoping Review

Improving Large Language Model Applications in the Medical and Nursing Domains With Retrieval-Augmented Generation: Scoping Review

Authors of this article:

Yiqun Miao1 Author Orcid Image ;   Yuhan Zhao1 Author Orcid Image ;   Yuan Luo1 Author Orcid Image ;   Huiying Wang1 Author Orcid Image ;   Ying Wu1, 2 Author Orcid Image
Article Authors Cited by (10) Tweetations Metrics

Journals

  1. Guiducci L, Saulle C, Dimitri G, Valli B, Alpini S, Tenti C, Rizzo A. Dialogical AI for Cognitive Bias Mitigation in Medical Diagnosis. Applied Sciences 2026;16(2):710 View
  2. Khalil R, Ahmad K, Ali H. Redefining Elderly Care With Agentic AI: Challenges and Opportunities. IEEE Open Journal of the Computer Society 2026;7:326 View
  3. Lin S, Shao S, Liu X, Su H. FusionGraphRAG: An Adaptive Retrieval-Augmented Generation Framework for Complex Disease Management in the Elderly. Information 2026;17(2):138 View
  4. Aljohani B, Alsanoosy T. Enhancing Medical Question Answering with LLMs via a Hybrid Retrieval-Augmented Generation Framework. Information 2026;17(2):133 View
  5. Coric R, Oloyede E, Cuayáhuitl H. Helpful or Harmful? Re-Evaluating Frugality in Retrieval-Augmented Generation for Medical Question Answering. Machine Learning and Knowledge Extraction 2026;8(3):64 View
  6. Schuh S, Schmidle P, Welzel J. Kooperation statt Konkurrenz. Deutsche Dermatologie 2026;74(3):212 View
  7. Abdur Rahman L, Dedousis V, Papathanail I, Poursoleymani R, Kafyra M, Kalafati I, Mougiakakou S. Generative AI in Precision Nutrition: A Review of Current Developments and Future Directions. Nutrients 2026;18(6):938 View
  8. El Ayat N, Boutalline M, Tannouche A, Ouazri C, Yahyaoui M. Dynamic-rag: a multimodal emotion-aware prompting and retrieval-augmented LLM framework for autism support in adaptive learning systems. Quality & Quantity 2026 View
  9. Tezcan H, Tunçez A, Gürses K, Özen Y, Yalçın M. Assessing the accuracy and educational value of ChatGPT-generated content for core topics in cardiology: a descriptive analysis at Selçuk University Cardiology Clinic. BMC Medical Education 2026 View

Conference Proceedings

  1. Karthik N, M M, Ebenezer V, Rajan J, Reeves S, SheebaThangapushpam C. 2026 Second International Conference on Multi-Agent Systems for Collaborative Intelligence (ICMSCI). RAG - In Hospital Management System View