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Dr. Farida Mohsen
PhD, Computer Science
Hamad Bin Khalifa University, Doha, Qatar
NowPostdoctoral Researcher, College of Science and Engineering, HBKU
Multimodal deep learning for diabetes risk prediction and diabetic retinopathy grading
About
Farida Mohsen’s doctoral research showed that combining retinal fundus images, ECG-derived features and clinical risk factors improves type 2 diabetes risk prediction in longitudinal Qatar Biobank cohorts. She developed ECG-DiaNet, a multimodal deep learning model, and RadEx, a nonlinear image transform released as open-source software.
Research interests
Four to eight research interests as short keywords
Thesis
Harnessing the Power of Artificial Intelligence: Predicting Type 2 Diabetes Onset
Abstract in about 100 words
Supervision: Dr. Zubair Shah
Projects 2
Publications with DAQIQ 10
The 5 most recent
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ECG features improve multimodal deep learning prediction of incident T2DM in a Middle Eastern cohort
Mohsen F, Safa A, Shah Z
Scientific Reports 15: 27164, 2025
Journal articleRead the paper Free version
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Integrating non-linear Radon transformation for diabetic retinopathy grading
Mohsen F, Belhaouari S, Shah Z
Scientific Reports 15: 30706, 2025
Journal articleRead the paper Free version
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RadEx: an open source Python package for nonlinear Radon transformation
Mohsen F, Islam A, Shah Z, Belhaouari SB
Software Impacts: 100779, 2025
Journal articleRead the paper
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A comparative evaluation of artificial intelligence-based models in retinal image synthesis
Mohsen F, Aldhubri A, Biswas MR, Shah Z
2nd International Conference on Foundation and Large Language Models (FLLM 2024): 51–57, 2024
Conference paperRead the paper Conference talk
Project and team
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Genetic biomarkers and machine learning techniques for predicting diabetes: systematic review
Khan S, Mohsen F, Shah Z
Artificial Intelligence Review 58(2): 41, 2024
Journal articleRead the paper