Predicting cognitive scores from wearable-based digital physiological features using machine learning: data from a clinical trial in mild cognitive impairment
Background: Continuous assessment and remote monitoring of cognitive function in individuals with mild cognitive impairment (MCI) enables tracking therapeutic effects and modifying treatment to achieve better clinical outcomes. While standardized neuropsychological tests are inconvenient for this pu...
Saved in:
Main Authors: | Rykov, Yuri G., Patterson, Michael D., Gangwar, Bikram A., Jabar, Syaheed B., Leonardo, Jacklyn, Ng, Kok Pin, Kandiah, Nagaendran |
---|---|
Other Authors: | Lee Kong Chian School of Medicine (LKCMedicine) |
Format: | Article |
Language: | English |
Published: |
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/174964 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Biomarkers of mild cognitive impairment and Alzheimer's disease
by: Tang, B.L., et al.
Published: (2011) -
Digital biomarkers for depression screening with wearable devices: cross-sectional study with machine learning modeling
by: Rykov, Yuri, et al.
Published: (2022) -
Usefulness of the visual cognitive assessment test in detecting mild cognitive impairment in the community
by: Soo, See Ann, et al.
Published: (2023) -
Predicting mild cognitive impairment through ambient sensing and artificial intelligence
by: TAN, Ah-hwee, et al.
Published: (2024) -
Commonalities in Biomarkers and Phenotypes Between Mild Cognitive Impairment and Cerebral Palsy: A Pilot Exploratory Study
by: Siang Ng, T.K., et al.
Published: (2022)