Recurrent Neural Network based Prediction of Transition to Mild Cognitive Impairment Using Unobtrusive Sensor Data
Author:
Affiliation:
1. Hindustan Institute of Technology and Science,Centre for Sensors and Process Control,Chennai,India
2. Tata Consultancy Services,Kolkata,INDIA
3. Rutgers School of Health Professions,Newark,NJ,USA
Funder
National Institute on Aging
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9915554/9915796/09915966.pdf?arnumber=9915966
Reference18 articles.
1. Intelligent Systems for Assessing Aging Changes: Home-Based, Unobtrusive, and Continuous Assessment of Aging
2. Corrigendum: Pervasive computing technologies to continuously assess Alzheimer's disease progression and intervention efficacy
3. Prevalence of Neuropsychiatric Symptoms in Dementia and Mild Cognitive Impairment
4. Symptoms of sleep disturbance in persons with Alzheimer's disease and normal elderly
5. In-home walking speeds and variability trajectories associated with mild cognitive impairment
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Predicting Mild Cognitive Impairment through Ambient Sensing and Artificial Intelligence;2024 IEEE Conference on Artificial Intelligence (CAI);2024-06-25
2. Employing Deep-Learning Approach for the Early Detection of Mild Cognitive Impairment Transitions through the Analysis of Digital Biomarkers;Sensors;2023-10-31
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