e.g. mhealth
Search Results (1 to 10 of 22 Results)
Download search results: CSV END BibTex RIS
Skip search results from other journals and go to results- 7 JMIR Research Protocols
- 4 JMIRx Med
- 4 Journal of Medical Internet Research
- 3 JMIR Medical Informatics
- 1 JMIR AI
- 1 JMIR Formative Research
- 1 JMIR Neurotechnology
- 1 JMIR XR and Spatial Computing
- 0 Medicine 2.0
- 0 Interactive Journal of Medical Research
- 0 iProceedings
- 0 JMIR Human Factors
- 0 JMIR Public Health and Surveillance
- 0 JMIR mHealth and uHealth
- 0 JMIR Serious Games
- 0 JMIR Mental Health
- 0 JMIR Rehabilitation and Assistive Technologies
- 0 JMIR Preprints
- 0 JMIR Bioinformatics and Biotechnology
- 0 JMIR Medical Education
- 0 JMIR Cancer
- 0 JMIR Challenges
- 0 JMIR Diabetes
- 0 JMIR Biomedical Engineering
- 0 JMIR Data
- 0 JMIR Cardio
- 0 Journal of Participatory Medicine
- 0 JMIR Dermatology
- 0 JMIR Pediatrics and Parenting
- 0 JMIR Aging
- 0 JMIR Perioperative Medicine
- 0 JMIR Nursing
- 0 JMIRx Bio
- 0 JMIR Infodemiology
- 0 Transfer Hub (manuscript eXchange)
- 0 Asian/Pacific Island Nursing Journal
- 0 Online Journal of Public Health Informatics
- 0 JMIR XR and Spatial Computing (JMXR)

Various neuroimaging techniques such as magnetic resonance imaging, functional magnetic resonance imaging (f MRI), positron emission tomography, and electroencephalography have been used for the early detection of AD [10]. Although f MRI is noninvasive and has good temporal and excellent spatial resolutions among functional neuroimaging methods, it has inherent limitations such as high cost, immobility due to heavy equipment, and vulnerability to head motion artifacts.
JMIR Res Protoc 2025;14:e66838
Download Citation: END BibTex RIS

They used ML models alongside multimodal neuroimaging data to classify various stages of AD progression. The findings from their investigation were highly encouraging, demonstrating pooled estimates for sensitivity of 94.6% and specificity of 93.5% in classifying patients with AD from healthy controls. This study demonstrates the considerable promise of ML algorithms when combined with multimodal neuroimaging biomarkers for differentiating patients with AD from cognitively normal (CN) individuals.
J Med Internet Res 2025;27:e62647
Download Citation: END BibTex RIS

Transformers for Neuroimage Segmentation: Scoping Review
Special study deserves transformer use in neuroimaging, as the structures of the brain are complicated. Neural networks based on transformers can model long-range dependencies and spatial relationships of the brain images [27], which is very important in brain segmentation.
Although transformers have shown very promising results in many medical imaging tasks, their use in neuroimaging segmentation remains an evolving field that had not been systematically reviewed.
J Med Internet Res 2025;27:e57723
Download Citation: END BibTex RIS
None of them used people with PD and neuroimaging tasks.
6. Still Introduction, fifth paragraph: The authors mention the Batson et al [13] study, but it would be relevant for this study to know with which type of and with how many participants this study was conducted.
Response: We have added that 1 participant was scanned and compared to the Fullerton Advanced Balance Scale. Thank you for this suggestion.
7.
JMIRx Med 2024;5:e67815
Download Citation: END BibTex RIS
Methods: “Study population – Neuroimaging sessions over 8-months”—how come the subsample of 10 people with PD has the same demographic characteristics as the total sample of 23 people with PD?
9. Results: a “reduction of GDS scores” is mentioned—I assume that GDS score reduction means improvement in depression symptoms? It would be important to mention this somewhere.
10.
JMIRx Med 2024;5:e67813
Download Citation: END BibTex RIS
Go back to the top of the page Skip and go to footer section

We assessed changes in the SCG using noninvasive neuroimaging for at least 2 time points over 8 months for each participant following a Df PD class, and we measured mood and depression before and after the dance class in the studio. Our findings suggest that participation in a nonmedical intervention (dance) may have the potential to modify emotional brain circuitry over time.
JMIRx Med 2024;5:e44426
Download Citation: END BibTex RIS

Neuroimaging methods, such as brain magnetic resonance imaging (MRI) and computerized axial tomography scans, are valuable tools to detect cerebrovascular pathology. Currently, lobar and deep CMB can only be identified by brain MRI. However, these imaging tools are costly and, in most cases, not accessible in rural areas and low-income contexts. There are over 50 million people estimated to live with dementia and AD worldwide, with the highest increases in lower- and middle-income countries [9].
J Med Internet Res 2024;26:e45780
Download Citation: END BibTex RIS

Participants were excluded if they had any intracranial abnormalities on neuroimaging. A separate cohort of healthy participants was enrolled from hospital staff using availability sampling over the same time period, which excluded those with self-reported known neurological disease or recent history of TBI.
JMIR Neurotech 2024;3:e58398
Download Citation: END BibTex RIS

Another preceding smaller meta-analysis of neuroimaging symptom provocation studies in OCD, conducted by Rotge et al [11], also found an increased likelihood of activation in 19 clusters in patients with OCD compared to healthy controls. These included the OFC, ACC, precuneus, and thalamus. Although paradigms have been developed to induce the urge to check in patients with OCD [12], to our knowledge, no provocation procedures to induce actual checking behavior have been applied in f MRI studies before.
JMIR XR Spatial Comput 2024;1:e47468
Download Citation: END BibTex RIS