9 papers
Leveraging Agonistic-Antagonistic Coactivation in Single-Grid HDsEMG for Hand Gesture Recognition
Firas Darwish, Dhiyaa Al Jorf, Costanza Armanini +2
Surface Electromyography (sEMG) is critical for intention prediction in human-computer interfaces, such as for prosthetics control. Although deep learning models for Hand Gesture R…
AgentRx: A Benchmark Study of LLM Agents for Multimodal Clinical Prediction Tasks
Baraa Al Jorf, Farah E. Shamout
Building effective clinical decision support systems requires the synthesis of complex heterogeneous multimodal data. Such modalities include temporal electronic health records dat…
Multimodal Deep Learning for Stroke Prediction and Detection using Retinal Imaging and Clinical Data
Saeed Shurrab, Aadim Nepal, Terrence J. Lee-St. John +3
Stroke is a major public health problem, affecting millions worldwide. Deep learning has recently demonstrated promise for enhancing the diagnosis and risk prediction of stroke. Ho…
MILES: Modality-Informed Learning Rate Scheduler for Balancing Multimodal Learning
Alejandro Guerra-Manzanares, Farah E. Shamout
The aim of multimodal neural networks is to combine diverse data sources, referred to as modalities, to achieve enhanced performance compared to relying on a single modality. Howev…
BlendFL: Blended Federated Learning for Handling Multimodal Data Heterogeneity
Alejandro Guerra-Manzanares, Omar El-Herraoui, Michail Maniatakos +1
One of the key challenges of collaborative machine learning, without data sharing, is multimodal data heterogeneity in real-world settings. While Federated Learning (FL) enables mo…
MedArabiQ: Benchmarking Large Language Models on Arabic Medical Tasks
Mouath Abu Daoud, Chaimae Abouzahir, Leen Kharouf +3
Large Language Models (LLMs) have demonstrated significant promise for various applications in healthcare. However, their efficacy in the Arabic medical domain remains unexplored d…