Correlating Multimodal Signals with Asthma Control in Children Using kHealth Personalized Digital Health System
Document Type
Abstract
Publication Date
5-18-2018
Identifier/URL
136361466 (Orcid)
Abstract
In United States, 6.3 million children suffer from asthma. The objective of this clinical trial is to evaluate effectiveness of extensive types of patient-generated health data (PGHD) and passively sensed data (collectively called multimodal signals), and thie processing using Artificial Intelligence (AI) and data analysis techniques for augmented personalized health care that supports personalized disease understanding (e.g., which factors are significant for a specific patient), self assessment and control in children with asthma.
Repository Citation
Kalra, M. S.,
Sheth, A.,
Banerjee, T.,
Jaimini, U.,
Kadariya, D.,
Sridharan, V.,
Thirunarayan, K.,
Venkataramanan, R.,
& Yip, H. Y.
(2018). Correlating Multimodal Signals with Asthma Control in Children Using kHealth Personalized Digital Health System. ATS 2018 International Conference, 2018, A60, 197.
https://corescholar.libraries.wright.edu/cse/649
