Project ID: 179
Cube proposed by: Satinder Singh Baveja
Cycle: MCubed 1.0
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About this project:
Home-based patient care and outcomes can be substantially improved via automated health communications over mobile devices. Current state of the art involves experts writing down elaborate flowcharts or rules that prescribe what message is sent under what conditions. At best such health communication can be responsive to a small number of health variables and at worst such health communication is unresponsive to individual patient experience and conditions. This project is about the use of automated and data-driven reinforcement learning (or machine learning for sequential decision-making) techniques to make health communications adaptive to the patient's experience and conditions. The end result would be tailored/personalized health communication that should be more effective at improving health outcomes.