Emergence of digital biomarkers to predict and modify treatment efficacy: machine learning study
Objectives Development of digital biomarkers to predict treatment response to a digital behavioural intervention.Design Machine learning using random forest classifiers on data generated through the use of a digital therapeutic which delivers behavioural therapy to treat cardiometabolic disease. Dat...
Saved in:
| Main Authors: | Nicole L Guthrie, Jason Carpenter, Katherine L Edwards, Kevin J Appelbaum, Sourav Dey, David M Eisenberg, David L Katz, Mark A Berman |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2019-07-01
|
| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/9/7/e030710.full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Attempt for an Emergent Scenario with Modified Chaplygin Gas
by: Sourav Dutta, et al.
Published: (2016-01-01) -
Therapeutic potential of microRNAs in neurological disorders: mechanisms, biomarkers, and emerging therapeutic strategies
by: Sourav Pal, et al.
Published: (2025-07-01) -
Emerging Clinical Perspectives of Immunotherapy in Triple Negative Breast Cancer: A Comprehensive Review
by: Sparshita Dey, et al.
Published: (2025-06-01) -
Exploring Emerging and Innovative Biomarkers for the Assessment and Monitoring of Cardiovascular Disease Risk and Treatment Efficacy in Patients
by: Omar Elsaka
Published: (2025-03-01) -
Modified blood cell GAP model as a prognostic biomarker in idiopathic pulmonary fibrosis
by: Michael Kreuter, et al.
Published: (2024-07-01)