PhD student Moza bint Talib Al-Adawi from the Department of Physiology, College of Medicine and Health Sciences, participated in the European Society of Cardiology (ESC) Congress 2026 in Munich, Germany, where she presented her research on the prediction of ventricular tachycardia in high-risk patients with hypertrophic cardiomyopathy.

Al-Adawi presented an e-poster entitled “Electrocardiogram-Based Deep Learning Model for Prediction of Ventricular Tachycardia in High-Risk Patients with Hypertrophic Cardiomyopathy”. The research explores the potential of combining electrocardiogram (ECG) data with deep learning to predict future ventricular tachycardia among high-risk patients with hypertrophic cardiomyopathy (HCM).

The findings indicate that the proposed model may provide a promising ECG-based approach for identifying patients at increased risk of developing ventricular tachycardia. By leveraging advances in deep learning, ECG analysis could complement existing risk stratification strategies and support earlier identification of patients who may require closer clinical assessment.

Al-Adawi’s research was conducted under the supervision of Prof. Khamis bin Mohammed Al-Hashmi, Dr. Mohammed bin Najeeb Al-Rawahi and Prof. Mohammed bin Abdullah Al-Abri.

The ESC Congress is one of the world’s leading international cardiovascular conferences, bringing together cardiologists, researchers, healthcare professionals and scientists to discuss advances in cardiovascular science and clinical practice.

Participation in the congress provided an opportunity to present research from SQU to an international scientific audience, exchange knowledge with researchers and gain insights into recent developments in cardiology and cardiovascular research. It also enabled Al-Adawi to establish scientific connections and explore perspectives that may contribute to the further development of her ongoing research.

The participation reflects SQU’s commitment to supporting postgraduate students and encouraging their engagement with international scientific and research platforms.