Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Shayok Chakraborty

Showing results (1-10 of 10) with videos related to

Pageof 1
Sort By:
IEEE Transactions on Neural Networks and Learning Systems|October 8, 2014
Adaptive Batch Mode Active LearningShayok Chakraborty, Vineeth Balasubramanian, Sethuraman Panchanathan
IEEE Transactions on Pattern Analysis and Machine Intelligence|September 10, 2015
Active Batch Selection via Convex Relaxations with Guaranteed Solution BoundsShayok Chakraborty, Vineeth Balasubramanian, Qian Sun, et al.
Plos One|October 2, 2024
Predicting adherence to gamified cognitive training using early phase game performance data: Towards a just-in-time adherence promotion strategyYuanying Pang, Ankita Singh, Shayok Chakraborty, et al.
JMIR Aging|March 18, 2026
Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults Using Source-Free Domain Adaptation: Algorithm Development and ValidationRonast Subedi, Shayok Chakraborty, Zhe He, et al.
JMIR Aging|September 16, 2024
Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults: Study of Domain Adaptation and Deep LearningAnkita Singh, Shayok Chakraborty, Zhe He, et al.
Contemporary Clinical Trials|August 24, 2025
Introducing the Adherence Promotion with Person-centered Technology (APPT) trial: Rationale, methods, and baseline characteristicsShenghao Zhang, Michael Dieciuc, Andrew Dilanchian, et al.
Information Processing & Management|August 1, 2022
A Machine-Learning Based Approach for Predicting Older Adults' Adherence to Technology-Based Cognitive TrainingZhe He, Shubo Tian, Ankita Singh, et al.
Frontiers in Psychology|December 5, 2022
Deep learning-based predictions of older adults' adherence to cognitive training to support training efficacyAnkita Singh, Shayok Chakraborty, Zhe He, et al.
BMC Digital Health|March 17, 2025
New Opportunities for the Early Detection and Treatment of Cognitive Decline: Adherence Challenges and the Promise of Smart and Person-Centered TechnologiesZhe He, Michael Dieciuc, Dawn Carr, et al.
The Gerontologist|March 10, 2022
Motivation to Engage in Aging Research: Are There Typologies and Predictors?Dawn C Carr, Shubo Tian, Zhe He, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
IEEE Transactions on Neural Networks and Learning Systems|October 8, 2014
Adaptive Batch Mode Active LearningShayok Chakraborty, Vineeth Balasubramanian, Sethuraman Panchanathan
IEEE Transactions on Pattern Analysis and Machine Intelligence|September 10, 2015
Active Batch Selection via Convex Relaxations with Guaranteed Solution BoundsShayok Chakraborty, Vineeth Balasubramanian, Qian Sun, et al.
Plos One|October 2, 2024
Predicting adherence to gamified cognitive training using early phase game performance data: Towards a just-in-time adherence promotion strategyYuanying Pang, Ankita Singh, Shayok Chakraborty, et al.
JMIR Aging|March 18, 2026
Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults Using Source-Free Domain Adaptation: Algorithm Development and ValidationRonast Subedi, Shayok Chakraborty, Zhe He, et al.
JMIR Aging|September 16, 2024
Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults: Study of Domain Adaptation and Deep LearningAnkita Singh, Shayok Chakraborty, Zhe He, et al.
Contemporary Clinical Trials|August 24, 2025
Introducing the Adherence Promotion with Person-centered Technology (APPT) trial: Rationale, methods, and baseline characteristicsShenghao Zhang, Michael Dieciuc, Andrew Dilanchian, et al.
Information Processing & Management|August 1, 2022
A Machine-Learning Based Approach for Predicting Older Adults' Adherence to Technology-Based Cognitive TrainingZhe He, Shubo Tian, Ankita Singh, et al.
Frontiers in Psychology|December 5, 2022
Deep learning-based predictions of older adults' adherence to cognitive training to support training efficacyAnkita Singh, Shayok Chakraborty, Zhe He, et al.
BMC Digital Health|March 17, 2025
New Opportunities for the Early Detection and Treatment of Cognitive Decline: Adherence Challenges and the Promise of Smart and Person-Centered TechnologiesZhe He, Michael Dieciuc, Dawn Carr, et al.
The Gerontologist|March 10, 2022
Motivation to Engage in Aging Research: Are There Typologies and Predictors?Dawn C Carr, Shubo Tian, Zhe He, et al.
Pageof 1