Raja Ebsim

Raja Ebsim is a Research Associate (Machine Learning) in the Division of Informatics, Imaging & Data Sciences at the School of Health Sciences, University of Manchester. His work focuses on applying machine learning techniques to medical imaging data, particularly in the context of osteoarthritis and bone health.

His research interests include:

• Machine Learning for Medical Imaging
• Osteoarthritis Diagnosis and Progression
• Hip and Knee Fracture Risk Prediction
• Genome-wide Association Studies in Bone Morphology
• Analysis of Large-scale Biomedical Datasets (e.g., UK Biobank)

Raja Ebsim's recent publications demonstrate a strong trend in leveraging dual-energy X-ray absorptiometry (DXA) images and genetic data to develop predictive biomarkers for joint replacement and fractures. His work often involves large cohort studies, such as the UK Biobank, and integrates multimodal data including imaging, demographic, and genetic information. The research has significant implications for early diagnosis and personalized treatment in orthopedics.

Raja Ebsim has been actively involved in conferences, including presenting a poster at AI UK 2023. His doctoral thesis, completed in 2019, focused on the automatic detection of wrist fractures in radiographs.

He collaborates extensively with researchers at the University of Manchester, including Prof. Tim Cootes and Dr. Clemens Lindner, on projects related to musculoskeletal health and imaging biomarkers.