activity
20222026
most citedIs it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models?

7 citations · 11 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2026

HEad and neCK TumOR (HECKTOR) 2025: Benchmark of Segmentation, Diagnosis, and Prognosis in Multimodal PET/CT

Numan Saeed, Salma Hassan, Shahad Hardan +27

Head and neck cancers (HNC) represent a significant global health burden, with accurate tumor delineation being essential for effective radiotherapy planning. The complexity of the…

cs.CV2025

A Multimodal and Multi-centric Head and Neck Cancer Dataset for Segmentation, Diagnosis and Outcome Prediction

Numan Saeed, Salma Hassan, Shahad Hardan +40

We present a publicly available multimodal dataset for head and neck cancer research, comprising 1123 annotated Positron Emission Tomography/Computed Tomography (PET/CT) studies fr…

cs.LG2025

Forget-MI: Machine Unlearning for Forgetting Multimodal Information in Healthcare Settings

Shahad Hardan, Darya Taratynova, Abdelmajid Essofi +2

Privacy preservation in AI is crucial, especially in healthcare, where models rely on sensitive patient data. In the emerging field of machine unlearning, existing methodologies st…

eess.IV2025

crossMoDA Challenge: Evolution of Cross-Modality Domain Adaptation Techniques for Vestibular Schwannoma and Cochlea Segmentation from 2021 to 2023

Navodini Wijethilake, Reuben Dorent, Marina Ivory +38

The cross-Modality Domain Adaptation (crossMoDA) challenge series, initiated in 2021 in conjunction with the International Conference on Medical Image Computing and Computer Assist…

cs.CV2025★ 2 cited

Efficient Parameter Adaptation for Multi-Modal Medical Image Segmentation and Prognosis

Numan Saeed, Shahad Hardan, Muhammad Ridzuan +3

Cancer detection and prognosis relies heavily on medical imaging, particularly CT and PET scans. Deep Neural Networks (DNNs) have shown promise in tumor segmentation by fusing info…

cs.LG2023★ 1 cited

Understanding Breast Cancer Survival: Using Causality and Language Models on Multi-omics Data

Mugariya Farooq, Shahad Hardan, Aigerim Zhumbhayeva +3

The need for more usable and explainable machine learning models in healthcare increases the importance of developing and utilizing causal discovery algorithms, which aim to discov…

eess.IV2023

Weakly Unsupervised Domain Adaptation for Vestibular Schwannoma Segmentation

Shahad Hardan, Hussain Alasmawi, Xiangjian Hou +1

Vestibular schwannoma (VS) is a non-cancerous tumor located next to the ear that can cause hearing loss. Most brain MRI images acquired from patients are contrast-enhanced T1 (ceT1…

cs.LG2022★ 1 cited

Energy Pricing in P2P Energy Systems Using Reinforcement Learning

Nicolas Avila, Shahad Hardan, Elnura Zhalieva +2

The increase in renewable energy on the consumer side gives place to new dynamics in the energy grids. Participants in a microgrid can produce energy and trade it with their peers…

eess.IV2022★ 7 cited

Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models?

Numan Saeed, Shahad Hardan, Kudaibergen Abutalip +1

Glioblastoma is a common brain malignancy that tends to occur in older adults and is almost always lethal. The effectiveness of chemotherapy, being the standard treatment for most…