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Ongoing Research

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AI2Equity: AI Integrating Social Determinants of Health to Advance Health Equity in Cardiovascular Risk Prediction(NIH: 1R01HL171599-01; PI: Liu) 4/2024-3/2028

Major Goals: There is a pressing need to address health disparities in cardiovascular disease (CVD). This study will use machine learning to develop a novel CVD risk prediction model that considers social determinants of health, structural social factors, and clinical factors, as well as their complex interactions. The model will be designed to be equitable, interpretable, and generalizable across diverse populations.  

Aim Ahead: DETERMINE: Diabetes prediction and equity through responsible machine learning(U of North Texas HSC/NIH:1OT2OD032581; PI: Liu) 09/2023-09/2025

The overarching goal of this project is to build an AI-powered, equitable, interpretable, actionable, and generalizable diabetes risk prediction model.

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  • iDAPT: Implementation & Informatics Developing Adaptable Process and Technologies for Cancer Control (NCI P50CA244693) 09/18/2023-08/31/2024

    The iDAPT Developing Cancer Center (Award Number: P50CA244693) is part of a newly formed national network of collaborative research centers, funded by the National Cancer Institute and supported through the Beau Biden Cancer Moonshot SM Initiative.  The iDAPT Developing Cancer Center, led by Drs. Kristie Foley and Thomas Houston from the Wake Forest School of Medicine and Dr. Sarah Cutrona from the University of Massachusetts Chan Medical School is a Developing Implementation Science Center for Cancer Control that will use technologies to support rapid cycle and real-time deployment and testing implementation processes and adaptations within cancer control. The iDAPT team focuses on building capacity among primary care and oncology partners to engage in implementation science in cancer control and to conduct pilot studies aligned with iDAPT's theme.

    ActivityChoice: A clinic-delivered implementation program to increase physical activity and decrease cardiovascular disease risk amongst cancer suvivors(NHLBI K01HL163254)

    The goal of ActivityChoice, led by Dr. Jamie Faro, is to develop and pilot test a clinic-based implementation program using patient narrative decision aids to support choices to a group in-person, group virtual, or self-monitored digital health physical activity program.

    Integrating Cancer Survivorship Care into Primary Care(UMCCTS PPP) 06/01/2023-05/31/2024

    Led by Dr. Jamie Faro, this project is a collaboration between primary care providers, cancer care providers, healthcare administration, and health IT. The objective is to understand the current state of post-treatment survivorship care at UMass Memorial, identify barriers to care communication, and develop strategies to improve care pathways. The overall goal is to improve cancer survivor's quality of care as they transition back to their primary care provider.