Mapping the landscape of machine learning in chronic disease management: A comprehensive bibliometric study
Objective This study aims to reveal global advancements and trends in machine learning (ML) for chronic disease management through a comprehensive bibliometric analysis, identifying research priorities to guide deeper exploration in the future. Methods Relevant documents on ML and chronic disease ma...
Saved in:
| Main Authors: | Shiying Shen, Wenhao Qi, Sixie Li, Jianwen Zeng, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Qian Xu, Shihua Cao |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-07-01
|
| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076251361614 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review
by: ShiYing Shen, et al.
Published: (2025-08-01) -
Mapping knowledge landscapes and emerging trends in digital biomarkers for dementia in older adults: A scoping and bibliometric analysis
by: Azliyana Azizan, et al.
Published: (2025-06-01) -
Mapping the research landscape of microRNAs in pain: a comprehensive bibliometric analysis
by: Huaiming Wang, et al.
Published: (2024-12-01) -
Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait
by: Wenhao Qi, et al.
Published: (2025-05-01) -
Mapping the research landscape of mHealth and technology in pediatric chronic illness: a bibliometric study
by: Esther Rodríguez-Jiménez, et al.
Published: (2025-03-01)