Congratulations to two students of DoM's Drs. Ross Mitchell, Mohamed Abdalla and Randy Goebel on winning the 2025 Young Innovators Competition

Congratulations to AI in Health students, Yasmin Madani Shamami in the PHAIR lab and Nafisa Sadaf Hriti in Dr. Goebel's lab for their work on frailty!

19 March 2025

Two students affiliated with the Precision Health AI Research Lab won the Grand Prize at the 4th Annual Young Innovators Competition at the ºÚÁϲ»´òìÈ (U of A). The competition offers a platform for U of A’s brightest minds to present their clinically translatable innovations in a high-energy, “Shark Tank”-style pitch competition. Six finalist teams showcased their innovative ideas for AI-powered healthcare solutions in front of a panel of expert judges. The Grand Prize was $1,000.

Winners:

  • Yasmin Madani Shamami, Computer Science MSc student in the PHAIR lab.
  • Nafisa Sadaf Hriti, Computer Science MSc student in Dr. Goebel’s lab

Supervisors:

  • Technical supervision by
    • Dr. Ross Mitchell, Professor, Division of General Internal Medicine
    • Dr. Mohamed Abdalla, Assistant Professor, Division of General Internal Medicine
    • Dr. Randy Goebel. Adjunct Professor, Division of Gastroenterology

  • Clinical supervision by Drs. Marjan Abbasi and Sheny Khera.

The Pitch:

Unraveling Frailty: Detection and Explanation from Clinical Text

In this talk, we will explore the pressing health challenge of frailty in older adults, a condition that significantly increases vulnerability to adverse health outcomes. With the aging population projected to double by 2050, early detection and intervention are crucial. We will discuss our innovative solution that leverages large language models (LLMs) to automate frailty assessment by analyzing clinical notes and electronic medical records. Our approach integrates natural language processing with explainable AI (XAI) techniques, enhancing both the accuracy and interpretability of frailty evaluations.

The presentation will highlight our mixed-methods study designed to validate the system’s effectiveness and usability within clinical workflows, aiming to reduce clinician workload while improving patient outcomes. We will address the challenges of AI adoption in healthcare, including trust, bias, and data privacy, and outline our strategies for ensuring ethical and equitable performance. Join us as we envision a future where AI-driven insights empower clinicians to deliver personalized care and optimize resource allocation in the fight against frailty.