Other Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

A Review Of Racial Differences And Disparities In Ecg, Jianwei Zheng, Chizobam Ani, Islam Abudayyeh, Yunfan Zheng, Cyril Rakovski, Ehsan Yaghmaei, Omolola Ogunyemi

Mathematics, Physics, and Computer Science Faculty Articles and Research

The electrocardiogram (ECG) is a widely used, non-invasive tool for diagnosing a range of cardiovascular conditions, including arrhythmia and heart disease-related structural changes. Despite its critical role in clinical care, racial and ethnic differences in ECG readings are often underexplored or inadequately addressed in research. Variations in key ECG parameters, such as PR interval, QRS duration, QT interval, and T-wave morphology, have been noted across different racial groups. However, the limited research in this area has hindered the development of diagnostic criteria that account for these differences, potentially contributing to healthcare disparities, as ECG interpretation algorithms largely developed from major …

Learning From Leads: A 1d Dilated Resnet For Ecg Chagas Disease Screening, Somesh Saini, Matheus Lima Diniz Araujo

Student Scholarship

No abstract provided.

A High Precision Machine Learning-Enabled System For Predicting Idiopathic Ventricular Arrhythmia Origins, Jianwei Zheng, Guohua Fu, Daniele Struppa, Islam Abudayyeh, Tahmeed Contractor, Kyle Anderson, Huimin Chu, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Background: Radiofrequency catheter ablation (CA) is an efficient antiarrhythmic treatment with a class I indication for idiopathic ventricular arrhythmia (IVA), only when drugs are ineffective or have unacceptable side effects. The accurate prediction of the origins of IVA can significantly increase the operation success rate, reduce operation duration and decrease the risk of complications. The present work proposes an artificial intelligence-enabled ECG analysis algorithm to estimate possible origins of idiopathic ventricular arrhythmia at a clinical-grade level accuracy.

Method: A total of 18,612 ECG recordings extracted from 545 patients who underwent successful CA to treat IVA were proportionally sampled into training, …

Ecg Monitoring In Athletes, Jalal Jwayyed, Kelly Purgason, Joseph Linder, Annamarie Alfery, Silvia Furman

Williams Honors College, Honors Research Projects

Athletes and medical personnel need reliable methods to monitor vital signs and detect potentially life-threatening issues before they occur. Electrocardiograph (ECG) monitors are currently the best method of detecting heart-related health issues. Current ECG monitors worn by athletes are difficult to use and lack the ability to track ECGs in real time. Through research and interviews with various clinicians, further problems have been identified that include poor electrode adhesion, and a lack of compatibility with the equipment worn by athletes. Our team proposes to develop solutions that will improve performance and comfort associated with ECG monitors for athletic applications. This …

Real-World Relevance Of Manual Electrocardiography Qt Interval Measurement, Satish Velagapudi, Zahra Nur Khaled, Bilal Omery, Firas Zahwe, Michael Anigbogu, Sarah Zukkoor, Indrajit Choudhuri

Journal of Patient-Centered Research and Reviews

Background: Electrocardiography (ECG) QT interval (QTI) prolongation independently predicts sudden death. Hospitalized patients are commonly exposed to multiple QT-prolonging drugs, and manual measurement of ECG QTI based on identifying the intersection of isoelectricity with the tangent to the terminal phase T-wave slope (QTTTT) is advocated due to inaccuracies in automated detection algorithms that may imprecisely identify QT duration.

Purpose: We evaluated the performance of QTTTT compared to a standard automated (12SL, GE Healthcare) method (QT-12SL).

Methods: Consecutively obtained ECGs of 250 hospitalized patients were reviewed. The QTI in leads II, aVR, V5 and V6 determined by QT-12SL and QTTTT were …