Search Results (1 to 10 of 1490 Results)
Download search results: CSV END BibTex RIS
Skip search results from other journals and go to results- 570 Journal of Medical Internet Research
- 173 JMIR Public Health and Surveillance
- 142 JMIR mHealth and uHealth
- 139 JMIR Medical Informatics
- 113 JMIR Formative Research
- 92 JMIR Research Protocols
- 52 JMIR Serious Games
- 29 Online Journal of Public Health Informatics
- 28 JMIR Human Factors
- 22 Interactive Journal of Medical Research
- 21 JMIR Cancer
- 14 JMIR Mental Health
- 13 JMIR AI
- 13 JMIR Aging
- 12 JMIR Medical Education
- 12 JMIR Pediatrics and Parenting
- 8 JMIR Infodemiology
- 7 JMIR Dermatology
- 6 Iproceedings
- 6 JMIR Diabetes
- 4 JMIR Bioinformatics and Biotechnology
- 4 JMIR Cardio
- 4 JMIR Nursing
- 3 JMIR Perioperative Medicine
- 1 Asian/Pacific Island Nursing Journal
- 1 JMIR Biomedical Engineering
- 1 JMIR Rehabilitation and Assistive Technologies
- 0 Medicine 2.0
- 0 iProceedings
- 0 JMIR Preprints
- 0 JMIR Challenges
- 0 JMIR Data
- 0 Journal of Participatory Medicine
- 0 JMIRx Med
- 0 JMIRx Bio
- 0 Transfer Hub (manuscript eXchange)
- 0 JMIR Neurotechnology
- 0 JMIR XR and Spatial Computing (JMXR)
Go back to the top of the page Skip and go to footer section
Go back to the top of the page Skip and go to footer section
Go back to the top of the page Skip and go to footer section
Go back to the top of the page Skip and go to footer section
Go back to the top of the page Skip and go to footer section
Large Language Models in Medical Diagnostics: Scoping Review With Bibliometric Analysis
For instance, Xiong et al [142] created Doctor GLM, a large-scale language model trained on a comprehensive Chinese health care database. Doctor GLM features a prompt designer module that extracts relevant keywords from user input, uses potential disease names as labels, and generates detailed descriptions based on a disease knowledge library. Therefore, Doctor GLM can provide users with accurate and reliable information, including disease symptoms, diagnoses, treatment options, and preventive measures.
J Med Internet Res 2025;27:e72062
Download Citation: END BibTex RIS
Go back to the top of the page Skip and go to footer section
Go back to the top of the page Skip and go to footer section
When compared to prior deep learning–based approaches, our method significantly outperforms the BERT–deep neural network (DNN) model of Chen et al [43] in mortality prediction. Specifically, our LLM with RAG integration achieved a substantially higher macro F1-score (0.7222, 95% CI 0.6998-0.7446) compared to their model (0.307, 95% CI 0.269-0.342), indicating a superior balance between precision and recall across both mortality and survival classes.
J Med Internet Res 2025;27:e75052
Download Citation: END BibTex RIS
Go back to the top of the page Skip and go to footer section