Search Results (1 to 10 of 1899 Results)
Download search results: CSV END BibTex RIS
Skip search results from other journals and go to results- 663 Journal of Medical Internet Research
- 202 JMIR Public Health and Surveillance
- 170 JMIR mHealth and uHealth
- 164 JMIR Formative Research
- 162 JMIR Research Protocols
- 144 JMIR Medical Informatics
- 53 JMIR Serious Games
- 46 Online Journal of Public Health Informatics
- 43 JMIR Human Factors
- 34 JMIR Mental Health
- 31 JMIR Cancer
- 28 Interactive Journal of Medical Research
- 21 JMIR Aging
- 20 JMIR Medical Education
- 20 JMIR Pediatrics and Parenting
- 16 Iproceedings
- 15 JMIR AI
- 14 JMIR Diabetes
- 10 JMIR Dermatology
- 9 JMIR Infodemiology
- 8 JMIR Cardio
- 5 JMIR Nursing
- 5 JMIR Perioperative Medicine
- 4 JMIR Bioinformatics and Biotechnology
- 4 JMIR Rehabilitation and Assistive Technologies
- 4 Journal of Participatory Medicine
- 1 Asian/Pacific Island Nursing Journal
- 1 JMIR Biomedical Engineering
- 1 JMIR Neurotechnology
- 1 Medicine 2.0
- 0 iProceedings
- 0 JMIR Preprints
- 0 JMIR Challenges
- 0 JMIR Data
- 0 JMIRx Med
- 0 JMIRx Bio
- 0 Transfer Hub (manuscript eXchange)
- 0 JMIR XR and Spatial Computing (JMXR)
Go back to the top of the page Skip and go to footer section

For example, Chen et al [23] developed a diagnostic model for sarcopenia based on age, cross-sectional area changes, and shear wave elasticity value changes, yielding an AUC of 0.883. Tang et al [24] developed an ultrasound-derived muscle assessment system based on muscle thickness, handgrip strength, and gait speed. The system had an overall diagnostic sensitivity of 92.7% and a specificity of 91% for sarcopenia.
J Med Internet Res 2025;27:e70545
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
Go back to the top of the page Skip and go to footer section

Implementation of Telemedicine for Patients With Dementia and Their Caregivers: Scoping Review
J Med Internet Res 2025;27:e65667
Download Citation: END BibTex RIS
Go back to the top of the page Skip and go to footer section

Based on data from the validation cohort, Chen et al [19] noted that the ML model based on both radiomics and CFs achieved the highest C-index of 0.869 (95% CI 0.783-0.955), with SEN and SPC of 0.759 and 0.821. Additional studies are warranted to corroborate the use of radiomics for tumor grading.
As for the training group, the pooled C-index of the CFs-based models was 0.726 (95% CI 0.662-0.790). SEN and SPC were not given in the included studies.
J Med Internet Res 2025;27:e69906
Download Citation: END BibTex RIS

Association Between Risk Factors and Major Cancers: Explainable Machine Learning Approach
JMIR Cancer 2025;11:e62833
Download Citation: END BibTex RIS
Go back to the top of the page Skip and go to footer section