Search Results (1 to 10 of 2285 Results)
Download search results: CSV END BibTex RIS
Skip search results from other journals and go to results- 644 Journal of Medical Internet Research
- 412 JMIR Research Protocols
- 269 JMIR Formative Research
- 193 JMIR mHealth and uHealth
- 103 JMIR Public Health and Surveillance
- 88 Online Journal of Public Health Informatics
- 70 JMIR Mental Health
- 67 JMIR Human Factors
- 62 JMIR Medical Informatics
- 49 JMIR Pediatrics and Parenting
- 38 JMIR Cancer
- 37 JMIR Serious Games
- 33 JMIR Aging
- 25 JMIR Medical Education
- 24 JMIR Dermatology
- 23 Iproceedings
- 22 JMIR Diabetes
- 18 Interactive Journal of Medical Research
- 18 JMIR Cardio
- 15 JMIR Perioperative Medicine
- 14 JMIR Infodemiology
- 14 Journal of Participatory Medicine
- 12 JMIR Rehabilitation and Assistive Technologies
- 10 JMIRx Med
- 8 JMIR AI
- 5 JMIR Biomedical Engineering
- 4 JMIR Neurotechnology
- 4 JMIR Nursing
- 2 JMIR XR and Spatial Computing (JMXR)
- 1 JMIR Bioinformatics and Biotechnology
- 1 Medicine 2.0
- 0 iProceedings
- 0 JMIR Preprints
- 0 JMIR Challenges
- 0 JMIR Data
- 0 JMIRx Bio
- 0 Transfer Hub (manuscript eXchange)
- 0 Asian/Pacific Island Nursing Journal

First, we trained a Continuous Bag of Words word2vec model on the entire corpus using the word2vec package in R (R Foundation for Statistical Computing) [27]. Next, we created a mental health vector by averaging the vectors of words strongly associated with mental health (eg, therapy, psychiatry, and diagnosis; see Multimedia Appendix 1 for details). This vector was used as a reference point for identifying mental health–related language.
J Med Internet Res 2025;27:e73950
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

Breath-Focused Mindfulness and Compassion Training in Parent-Child Dyads: Pilot Intervention Study
JMIR Form Res 2025;9:e69607
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
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

The results showed a moderate positive correlation (r=0.64) across all extracted features, which was statistically significant (P
Correlation between Chat GPT Features and IDL Features.
JMIR AI 2025;4:e68144
Download Citation: END BibTex RIS