6 citations · 6 across the 2 of their papers we have counts for
3 papers
cs.LG2026★ 6 cited
Automated detection of pediatric congenital heart disease from phonocardiograms using deep and handcrafted feature fusion
Abdul Jabbar, Ethan Grooby, Yang Yi Poh +5
Congenital heart disease (CHD) is the most common type of birth defect, impacting about 1% of live births worldwide. Echocardiography, the gold-standard diagnostic method, is costl…
eess.AS2025
Congenital Heart Disease Classification Using Phonocardiograms: A Scalable Screening Tool for Diverse Environments
Abdul Jabbar, Ethan Grooby, Jack Crozier +7
Congenital heart disease (CHD) is a critical condition that demands early detection, particularly in infancy and childhood. This study presents a deep learning model designed to de…
eess.IV2024
Skin Cancer Machine Learning Model Tone Bias
James Pope, Md Hassanuzzaman, William Chapman +5
Background: Many open-source skin cancer image datasets are the result of clinical trials conducted in countries with lighter skin tones. Due to this tone imbalance, machine learni…