4 papers
ModalSurv: Investigating opportunities and limitations of multimodal deep survival learning in prostate and bladder cancer
Noorul Wahab, Ethar Alzaid, Jiaqi Lv +3
Accurate survival prediction is essential for personalised cancer treatment. We propose ModalSurv, a multimodal deep survival framework integrating clinical, MRI, histopathology, a…
MPath: Multimodal Pathology Report Generation from Whole Slide Images
Noorul Wahab, Nasir Rajpoot
Automated generation of diagnostic pathology reports directly from whole slide images (WSIs) is an emerging direction in computational pathology. Translating high-resolution tissue…
A Deep Learning Framework for Thyroid Nodule Segmentation and Malignancy Classification from Ultrasound Images
Omar Abdelrazik, Mohamed Elsayed, Noorul Wahab +2
Ultrasound-based risk stratification of thyroid nodules is a critical clinical task, but it suffers from high inter-observer variability. While many deep learning (DL) models funct…
Synergy vs. Noise: Performance-Guided Multimodal Fusion For Biochemical Recurrence-Free Survival in Prostate Cancer
Seth Alain Chang, Muhammad Mueez Amjad, Noorul Wahab +3
Multimodal deep learning (MDL) has emerged as a transformative approach in computational pathology. By integrating complementary information from multiple data sources, MDL models…