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ShoU combines intelligent health monitoring tools with virtual access to healthcare providers. The platform enables users to track all relevant nutrition, exercise, and biometric data, while the provider network ensures accessible and affordable care.

Problem/Project Description:

Optimize the interaction between provider and patient to yield best health outcomes.

How is this problem at the intersection of human behavior and machine learning?

Providers use telemedicine channels (text, audio, video) to interact with patients and convey a prescription. Machine learning models can be used to identify the optimal type and frequency of interaction that drives prescription adherence (behavior change) in patients (eg. nutrition, exercise, smoking cessation, medications, etc.).

What part of your project requires a Machine Learning student:

Building models to optimize telemedicine interaction.

What part of your project requires a Human Behavioral and Learning student:

Vision for the application of machine learning model in driving behavioral health change as well as defining measures of success.

Specific Tasks and Expectations of the LUCID student (label % time for each task):

(Guideline for timeline: one summer, one semester and roughly 8-10hrs/week or 120 hours total)

To be determined.

Anticipated Deliverables:

Machine learning model that identifies optimal provider interaction for a given patient (or category of patients).

Contact information:

Brennan O’Connell

Email: Brennan.oconnell@shouhealth.com