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Professor Shijie Zhou Awarded American Heart Association Grant for AI-Driven VT Localization Project

A new project led by Prof. Shijie Zhou has been awarded an Innovative Project Award from the American Heart Association (AHA) to develop a non-invasive approach to localizing ventricular tachycardia (VT) exit sites, without the need for traditional QRS onset detection. Titled “Innovative Personalized AI for Automated, Non-invasive VT Exit Site Localization Without QRS Onset Selection,” this research aims to eliminate the subjectivity inherent in current methods of localizing VT exit sites using the QRS complex of 12-lead ECGs. By leveraging artificial intelligence and advanced signal processing, the study seeks to develop an automated framework that bypasses the need for manual QRS onset selection. This work aims to significantly improve the diagnostic precision and treatment safety for patients suffering from VT, a life-threatening heart rhythm disorder. The project is a collaborative effort that brings together leading experts in cardiac electrophysiology and biomedical research from across North America. The research team includes Dr. John Sapp and Dr. Amir AbdelWahab from QEII Health Sciences Centre in Canada, and Dr. Usha Tedrow and Dr. Paul Zei from Brigham and Women’s Hospital in Massachusetts. The AHA Innovative Project Award supports early-stage, highly innovative research that has the potential to transform cardiovascular science and care. This recognition highlights the potential of this AI-driven approach to reshape how VT is diagnosed and treated in the clinic.  

A new project led by Prof. Shijie Zhou has been awarded an Innovative Project Award from the American Heart Association (AHA) to develop a non-invasive approach to localizing ventricular tachycardia (VT) exit sites, without the need for traditional QRS onset detection.

Titled “Innovative Personalized AI for Automated, Non-invasive VT Exit Site Localization Without QRS Onset Selection,” this research aims to eliminate the subjectivity inherent in current methods of localizing VT exit sites using the QRS complex of 12-lead ECGs. By leveraging artificial intelligence and advanced signal processing, the study seeks to develop an automated framework that bypasses the need for manual QRS onset selection. This work aims to significantly improve the diagnostic precision and treatment safety for patients suffering from VT, a life-threatening heart rhythm disorder.

The project is a collaborative effort that brings together leading experts in cardiac electrophysiology and biomedical research from across North America. The research team includes Dr. John Sapp and Dr. Amir AbdelWahab from QEII Health Sciences Centre in Canada, and Dr. Usha Tedrow and Dr. Paul Zei from Brigham and Women’s Hospital in Massachusetts.

The AHA Innovative Project Award supports early-stage, highly innovative research that has the potential to transform cardiovascular science and care. This recognition highlights the potential of this AI-driven approach to reshape how VT is diagnosed and treated in the clinic.
 

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