Automated Diagnosis of Breast Cancer Using Deep Learning-Based Whole Slide Image Analysis of Molecular Biomarkers. - Ahmed Aboudessouki; Khadiga M. Ali; Mohamed Elsharkawy; Ahmed Alksas; Ali Mahmoud 001; Fahmi Khalifa; Mohammed Ghazal; Jawad Yousaf; Hadil Abu Khalifeh; Ayman El-Baz (ICIP, 2023)

Harnessing Vision Transformers for Precise and Explainable Breast Cancer Diagnosis. - Hossam Magdy Balaha; Khadiga M. Ali; Dibson D. Gondim; Mohammed Ghazal; Ayman El-Baz (ICPR (11), 2024)

Integrated Grading Framework for Histopathological Breast Cancer: Multi-level Vision Transformers, Textural Features, and Fusion Probability Network. - Hossam Magdy Balaha; Khadiga M. Ali; Ali Mahmoud 001; Mohammed Ghazal; Ayman El-Baz (ICPR (28), 2024)

Predicting Response to Neoadjuvant Chemotherapy using Multi-Modal MRI Radiomics and Machine Learning Approaches. - Abdelrahman Gamal; Ahmed Sharafeldeen; Eman Alnaghy; Reham Alghandour; Khadiga M. Ali; Sameh Shamaa; Amal Aboueleneen; Ahmed Elsaid Tolba; Samir Elmougy; Mohammed Ghazal; Sohail Contractor; Ayman El-Baz (ISBI, 2025)

Enhancing Breast Cancer Diagnosis With Multi-Resolution Vision Transformers and Robust Decision-Making. - Margo Sabry; Hossam Magdy Balaha; Khadiga M. Ali; Tayseer Hassan A. Soliman; Dibson D. Gondim; Mohammed Ghazal; Norah Saleh Alghamdi; Ayman El-Baz (IEEE Access, 2025)

A Comprehensive Deep Learning System With MGRF Modeling for Predicting Breast Cancer Response to Neoadjuvant Chemotherapy. - Ahmed Sharafeldeen; Fatma Taher; Norah Saleh Alghamdi; Eman Alnaghy; Reham Alghandour; Khadiga M. Ali; Sameh Shamaa; Abdelrahman Gamal; Mohammed Ghazal; Sohail Contractor; Ayman El-Baz (IEEE Access, 2025)