2 citations · 8 across the 13 of their papers we have counts for
13 papers
SurvCORN: Survival Analysis with Conditional Ordinal Ranking Neural Network
Muhammad Ridzuan, Numan Saeed, Fadillah Adamsyah Maani +2
Survival analysis plays a crucial role in estimating the likelihood of future events for patients by modeling time-to-event data, particularly in healthcare settings where predicti…
Introducing SDICE: An Index for Assessing Diversity of Synthetic Medical Datasets
Mohammed Talha Alam, Raza Imam, Mohammad Areeb Qazi +2
Advancements in generative modeling are pushing the state-of-the-art in synthetic medical image generation. These synthetic images can serve as an effective data augmentation metho…
PEMMA: Parameter-Efficient Multi-Modal Adaptation for Medical Image Segmentation
Nada Saadi, Numan Saeed, Mohammad Yaqub +1
Imaging modalities such as Computed Tomography (CT) and Positron Emission Tomography (PET) are key in cancer detection, inspiring Deep Neural Networks (DNN) models that merge these…
SurvRNC: Learning Ordered Representations for Survival Prediction using Rank-N-Contrast
Numan Saeed, Muhammad Ridzuan, Fadillah Adamsyah Maani +3
Predicting the likelihood of survival is of paramount importance for individuals diagnosed with cancer as it provides invaluable information regarding prognosis at an early stage.…
Byzantine-Tolerant Methods for Distributed Variational Inequalities
Nazarii Tupitsa, Abdulla Jasem Almansoori, Yanlin Wu +4
Robustness to Byzantine attacks is a necessity for various distributed training scenarios. When the training reduces to the process of solving a minimization problem, Byzantine rob…
A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection
Anas Al-lahham, Nurbek Tastan, Zaigham Zaheer +1
Detection of anomalous events in videos is an important problem in applications such as surveillance. Video anomaly detection (VAD) is well-studied in the one-class classification…