Houston organizations issue seed grants to fuel AI-driven equity, digital health innovation

fresh funding

Rice University, Baylor College of Medicine, and Houston Methodist have awarded a total of $50,000 to two projects. Photo by Brandon Martin/Rice University

Three Houston organizations have doled out seed grants for research initiatives focused on digital health and equity.

Rice University's Educational and Research Initiatives for Collaborative Health (ENRICH) office — in partnership with Baylor College of Medicine and the Houston Methodist Academic Institute — has awarded a total of $50,000 to two projects. BCM and Rice announced three other grants earlier this year.

The seed grants were deployed earlier this year at the Health Equity Workshop from Rice’s Digital Health Initiative and chaired by Momona Yamagami, an assistant professor of electrical and computer engineering at Rice.

“To achieve equitable health outcomes, a comprehensive approach is essential — one that spans all phases of digital health from technology design and development to implementation, dissemination and long-term sustainability,” says Ashutosh Sabharwal, who leads the Digital Health Initiative and serves as Rice’s Ernest Dell Butcher Professor of Engineering and a professor of electrical and computer engineering, in a news release.

Both the workshop and the grant opportunity help to allow collaboration between researchers and health care providers working on health equity research across disciplines.

“This seed grant not only fosters interdisciplinary collaborations between Rice University and the Texas Medical Center but also enables us to leverage our combined knowledge to enhance innovations in health equity and digital health, ultimately creating impactful solutions for improving patient care,” adds Sharon Pepper, executive director of ENRICH.

The two projects receiving funding, according to Rice's release, include:

  • Evaluating Equity and Community-Level Vulnerabilities in the Use of Generative Artificial Intelligence-based Symptom Checkers for Self-diagnosis — Using AI-based symptom checkers, the project aims to mitigate vulnerabilities for patients using and improve data precision specifically when it comes to patients' social and cultural differences.
  • Al-Driven ECG Analysis for Equitable Cardiovascular Risk Assessment and Prevention: Leveraging Transformer Models and Big Data to Reduce Health Disparities — Also backed by AI, this project will harness the untapped potential of electrocardiogram data for improving cardiovascular risk assessment, hopefully reducing cost and invasiveness of the standard practice of care.
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Until now, Rice students could study AI through elective courses and an advanced degree. The new bachelor's degree program opens up deeper learning opportunities to undergrads by blending traditional engineering and math requirements with other courses on ethics and philosophy as they relate to AI.

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