e.g. mhealth
Search Results (1 to 2 of 2 Results)
Download search results: CSV END BibTex RIS
Skip search results from other journals and go to results- 1 JMIR Formative Research
- 1 Journal of Medical Internet Research
- 0 Medicine 2.0
- 0 Interactive Journal of Medical Research
- 0 iProceedings
- 0 JMIR Research Protocols
- 0 JMIR Human Factors
- 0 JMIR Medical Informatics
- 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 Med
- 0 JMIRx Bio
- 0 JMIR Infodemiology
- 0 Transfer Hub (manuscript eXchange)
- 0 JMIR AI
- 0 JMIR Neurotechnology
- 0 Asian/Pacific Island Nursing Journal
- 0 Online Journal of Public Health Informatics
- 0 JMIR XR and Spatial Computing (JMXR)

Cat Boost: categorical boosting; Light GBM: light gradient boosting machine; MLP: multiplayer perceptron; SVM: support vector machine; XGBoost: extreme gradient boosting machine.
The SHAP analysis of the best-performing Cat Boost model is shown in Figure 4.
J Med Internet Res 2025;27:e73190
Download Citation: END BibTex RIS

Machine-Aided Self-diagnostic Prediction Models for Polycystic Ovary Syndrome: Observational Study
The goal of this proposed study is to develop a machine-aided self-diagnostic tool that predicts the diagnosis of PCOS with and without any invasive measures, using Principal Component Analysis (PCA), k-means clustering algorithm, and Cat Boost classifier. The Cat Boost method is one of the newer gradient boosting decision tree models, and it was recently used in diabetes prediction in the study by Kumar et al [20].
JMIR Form Res 2022;6(3):e29967
Download Citation: END BibTex RIS