Our research in the Health Informatics area aims to develop computer-based systems to improve the quality, efficiency, and cost-effectiveness of healthcare systems. The research focuses on utilizing IoT and AI to enhance diagnosis of diseases, and improve the reliability and security of eHealth systems.
Faculty Members:
Primary:
Khalid Abualsaud (mHealth)
Uvais Qidwai (AI for Health)
Saeed Salem (Bioinformatics)
Secondary:
Abdulaziz Al-Ali (AI for Health)
Abdulla Al-Ali (mHealth)
Cagatay Catal (AI for Health)
Junaid Qadir (AI for Health)
Elias Yaacoub (AI for Health, mHealth)
Saeed Salem (AI for health)
Mahmoud Barhamgi (Data Management)
Ahmed Badawy (mHealth, AI for health)
Related Projects:
NPRP13S-0205-200270: Privacy-Preserving Health Monitoring System Using AI and Non-Intrusive Smart Sensors
NPRP12S-0305-190231: Ultra Reliable Low Latency Smart Health System Design over 5G Networks for Patients with Neurological Disorders
NPRP10-1205-160012: Optimized Security for eHealth Internet of Things Systems
NPRP7-684-1-127: QHCN: Towards Reliable and Efficient mHealth System with Multimodal Processing and Communications for Effective Remote Patient Diagnosis
NPRP7-234-2-109: Novel Approaches in the Development and Application of Autonomous Robotic Approaches for the Structural Health Monitoring of Civil and Mechanical Infrastructure Systems
NPRP6-249-1-053: Automated Classification and Diagnosis of Tissue Patterns in Colorectal Tumours Using Non-Visible Multispectral Imagery
NPRP5-1345-1-228: Novel Prognostic Biomarkers for Colorectal Cancer via Computerized Analysis of Highly Multiplexed Protein Fluorescence Image Data
NPRP09-310-1-058: Innovative framework for scalable signal processing and power-efficient communication in healthcare wireless body area sensor networks