Search Results (1 to 10 of 321 Results)
Download search results: CSV END BibTex RIS
Skip search results from other journals and go to results- 56 Journal of Medical Internet Research
- 40 JMIR Formative Research
- 38 JMIR Public Health and Surveillance
- 35 JMIR Research Protocols
- 33 Iproceedings
- 18 JMIR mHealth and uHealth
- 16 JMIR Medical Informatics
- 15 JMIR Medical Education
- 13 JMIR Human Factors
- 9 Interactive Journal of Medical Research
- 8 Online Journal of Public Health Informatics
- 5 JMIR Serious Games
- 4 JMIR Aging
- 4 JMIR Diabetes
- 3 JMIR Cardio
- 3 JMIR Infodemiology
- 3 JMIR Nursing
- 3 JMIR Pediatrics and Parenting
- 3 JMIRx Med
- 2 JMIR Dermatology
- 2 JMIR Mental Health
- 2 Journal of Participatory Medicine
- 1 JMIR AI
- 1 JMIR Bioinformatics and Biotechnology
- 1 JMIR Cancer
- 1 JMIR Data
- 1 JMIR Rehabilitation and Assistive Technologies
- 1 Medicine 2.0
- 0 iProceedings
- 0 JMIR Preprints
- 0 JMIR Challenges
- 0 JMIR Biomedical Engineering
- 0 JMIR Perioperative Medicine
- 0 JMIRx Bio
- 0 Transfer Hub (manuscript eXchange)
- 0 JMIR Neurotechnology
- 0 Asian/Pacific Island Nursing Journal
- 0 JMIR XR and Spatial Computing (JMXR)
Authors’ Reply: Citation Accuracy Challenges Posed by Large Language Models
JMIR Med Educ 2025;11:e73698
Download Citation: END BibTex RIS
For example, a meta-analysis by Beleigoli et al [53] found that web-based interventions resulted in modest but significant additional weight loss compared with standard care. Moreover, our findings broaden the current literature on digital weight loss interventions that incorporate pharmacotherapy, building on recent work by Richards et al [29,30] which demonstrated that a remotely delivered, semaglutide-supported weight management program is both effective and efficacious in the short term.
J Med Internet Res 2025;27:e69466
Download Citation: END BibTex RIS
Banerjee et al [11] reported that postgraduate trainee doctors have an overall positive perception of the impact of AI on clinical training; however, they found that AI will eventually reduce the trainees’ clinical judgment and practical skills. In line with that, the faculty participants were concerned about students’ self-reliance on AI applications on the cost of traditional teaching methods, which might deprive them from skills best learned in person or group teaching.
JMIR Med Educ 2025;11:e63400
Download Citation: END BibTex RIS
Examining the Role of AI in Changing the Role of Nurses in Patient Care: Systematic Review
JMIR Nursing 2025;8:e63335
Download Citation: END BibTex RIS
For example, Yu et al [22] and Yu et al [23] proposed an automatic pill recognition method based on pill imprints, achieving an accuracy of 86.01% and 90.46%, respectively. Caban et al [18] used a modified shape distribution technique to determine the shape, color, and imprint of a pill to identify the drug. The proposed technique was evaluated with 568 of the most prescribed drugs in the United States and achieved a 91.13% accuracy.
JMIR Hum Factors 2025;12:e60273
Download Citation: END BibTex RIS
In addition, the research conducted by Lozano-Blasco et al [57] found that using lesser answer categories led to decreased Cronbach α values. The dichotomous character of the questions in the IADQ, which means that they only allow for replies of yes or no, leads to lower Cronbach α values that are within the acceptable range for dependability.
JMIR Hum Factors 2025;12:e62955
Download Citation: END BibTex RIS
Dynamic Augmented Reality Cues for Telementoring in Minimally Invasive Surgeries: Scoping Review
With respect to MIS, Nickel et al [23] provided a concise clinical summary, whereas others reported on the use of audio and static AR cues [16,17,19,34,35]. While these reviews offer a comprehensive understanding of telementoring during MIS, they do not highlight the developments in the use of dynamic AR cues. To the best of our knowledge, there has not yet been a systematic examination specifically on the use of dynamic AR cues used by remote mentors during telementoring in MIS.
J Med Internet Res 2025;27:e63939
Download Citation: END BibTex RIS
This study adapted and used a questionnaire previously tested and found valid and reliable by Forsea et al [25].
JMIR Dermatol 2025;8:e63861
Download Citation: END BibTex RIS
Go back to the top of the page Skip and go to footer section
Of the 25 studies reviewed, 20 (80%) opted to construct models using a dataset created by the authors, whereas 5 (20%) chose established benchmark datasets, such as the Floodlight Proof-of-Concept dataset used in the study by Creagh et al [45], the My Fitness Pal dataset used in the study by Harris et al [56], the MHEALTH dataset used in the study by Uddin and Soylu [49], the Continuous Glucose Monitoring Intervention in Teens and Young Adults With Type 1 Diabetes study dataset [70], and the Human Activity Recognition
J Med Internet Res 2024;26:e53863
Download Citation: END BibTex RIS