Zaied Alhaj

Heart sound classification using machine learning approaches based on mel-frequency cepstrum coefficients (MFCCs) and statistical features

Heart sounds provide a valuable non-invasive source of information for the early detection of cardiac abnormalities. However, reliably distinguishing normal from abnormal heart sounds remains challenging in routine clinical practice because interpretation depends strongly on expe...

Speckle aware attention and multi scale pooling for robust breast ultrasound lesion classification across multiple benchmarks

Breast ultrasound (BUS) is widely used for lesion assessment, yet automatic benign–malignant classification remains challenging owing to speckle noise, weak boundaries, and cross-scanner heterogeneity. We propose SUA-Net, a compact framework that augments an EfficientNet-B0 backb...

Patient-level topology-aware graph transformer for breast histopathology classification

Progress in computational pathology is limited not only by model architecture, but also by evaluation design. In breast histopathology benchmarks such as BreaKHis, multiple correlated image tiles often originate from the same patient; consequently, image-wise splits can inflate p...