Wearable AI system developed by Qatar medical students flags cardiac risk outside hospital

An 82.7 percent accuracy rate is not clinical validation. But for a system built by a first-year medical student and a recent graduate as part of a hackathon, it is a result worth paying attention to. Researchers at Weill Cornell Medicine-Qatar (WCM-Q) have published early findings on WearAware, an AI-assisted framework designed to detect cardiac abnormalities in patients outside hospital settings using wearable technology.

Dounia Baroudi, currently in her first year of medical school, and Dr. Amal Alnaemi, who graduated in May 2026, presented the paper at the 24th International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH), held in Athens. The paper has since been published in Studies in Health Technology and Informatics, a Scopus-indexed journal.

The project started as a challenge issued by Dr. Arfan Ahmed, assistant professor of research in population health sciences and director of wearable AI for precision health at WCM-Q, during a 2025 hackathon organized by the institution's AI Center for Precision Health. Dr. Ahmed then mentored the pair through the process of turning that initial concept into a peer-reviewed publication.

How does it work?

WearAware combines three components to create a continuous cardiac monitoring loop outside clinical settings:

• A smart patch worn by the patient to capture ECG and other cardiac signals
• An AI-driven alert system that analyzes those signals in real time
• A clinician portal that allows healthcare providers to review data remotely

The system is designed to give patients advance warning when their cardiac readings suggest they should seek medical attention. Early ECG testing showed the AI component achieved 82.7 percent accuracy. The authors are clear that WearAware is a proof-of-concept and has not yet been clinically validated, but the published results justify further investigation.

Why does it matter?

Cardiovascular disease remains one of the leading causes of death across the Gulf region and globally. A significant number of cardiac events happen outside hospitals, where there is no monitoring equipment and no immediate clinical oversight. That gap in coverage is exactly what WearAware is trying to address.

So the clinical question is straightforward: if a wearable device can reliably flag early warning signs and prompt a patient to seek care before a major event, outcomes improve. And the research question is equally important: can AI models built by clinicians with domain knowledge, rather than dedicated data scientists, produce results that hold up to peer review? In this case, the answer appears to be yes.

Dr. Ahmed put it plainly: "AI has changed things completely. What once required in-depth coding and computer science expertise no longer does, and we now have medical students here in Qatar building their own AI models."

The context

This research sits squarely within the broader push across the GCC to embed AI and digital health into healthcare delivery. Qatar's National Vision 2030 places health innovation at the center of long-term development goals, and institutions like WCM-Q are a key part of that strategy. The UAE has made similar moves through its national AI strategy and health digitization programs, with remote monitoring and preventive care increasingly central to regional health policy.

But beyond policy, what this project illustrates is something more practical: medical students in the region are no longer passive recipients of clinical education. They are producing research that reaches international conferences and indexed journals. Dr. Alnaemi and Baroudi are named authors alongside Dr. Ahmed and Dr. Eniola Olaleye, an AI systems engineer at Cornell University in the United States. The full paper is available here.

That kind of early-career output, tied to a real clinical problem and mentored through to publication, is exactly the model that health systems across the Gulf will need if they are serious about building local AI capability in medicine rather than importing it.