Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults: Study of Domain Adaptation and Deep Learning.
Ankita SinghShayok ChakrabortyJiang BianYuanying PangShenghao ZhangRonast SubediMia Liza A LustriaNeil CharnessWalter R BootPublished in: JMIR aging (2024)
Our findings highlight that deep learning and DA techniques can aid in the development of adherence support systems for computerized cognitive training, as well as for other interventions aimed at improving health, cognition, and well-being. These techniques can improve engagement and maximize the benefits of such interventions, ultimately enhancing the quality of life of individuals at risk for cognitive impairments. This research informs the development of more effective interventions, benefiting individuals and society by improving conditions associated with aging.
Keyphrases
- deep learning
- physical activity
- public health
- artificial intelligence
- convolutional neural network
- healthcare
- machine learning
- virtual reality
- mental health
- type diabetes
- adipose tissue
- multiple sclerosis
- glycemic control
- risk assessment
- health information
- clinical decision support
- health promotion
- electronic health record