DECIDE-CV Using AI

Delivering Evidence Based Care Using Artificial Intelligence to Patients With Diabetes and CardioVascular Comorbidities: The DECIDE-CV Innovation Project

The purpose of this study is to identify digital biomarkers associated with type 2 diabetes mellitus (T2DM) by combining sensor data from a wrist-worn wearable and clinical data. This will be done by recruiting patients with and without diabetes within the cardio-metabolic clinics a the MUHC. Consented patients will be provided with a HOP Technologies (HOP) watch in this project across two observation periods. The Watch-HOP platform facilitates the development of predictive algorithms built with data collected in a clinical setting or at home in a passive (sensors) and active (self-assessments) way. Data from the Watch-Hop will be analyzed using machine learning strategies to determine associations with clinical measures of T2DM.

The epidemic of type 2 diabetes mellitus (T2DM) continues to increase. Sensor technologies and artificial intelligence present us with an opportunity to identify patients suffering from T2DM and to optimize their treatment.

Specifically, our primary objective is to identify digital biomarkers associated with T2DM by combining sensor data from a wrist-worn wearable and clinical data.

Inclusion Criteria:

1. Age > 18 years
2. Able to follow-up with study protocol schedule
3. Life expectancy > 1 year
4. Case group only a. HbA1c >= 6.5% or is diagnosed with T2DM

Exclusion Criteria:

1. Any person who does not meet the above criteria or who refuses to participate
2. Undergoing chemotherapy or dialysis
3. Currently in palliative care
4. Any person who does not have an email address
5. Control group only a. HbA1c >= 6.5% or is diagnosed with T2DM