Square photo, 640 × 640 px
Dr. Sulaiman Khan
Research Assistant
Hamad Bin Khalifa University, Doha, Qatar
Longitudinal multimodal AI for early prediction of type 2 diabetes and its complications
About
Sulaiman Khan completed his PhD in Computer Science with DAQIQ and now works with the program as a Research Assistant.
His doctoral research fused imaging, ECG, genetic, laboratory and lifestyle data from Qatar Biobank to model how diabetes risk changes over time, and to study complication pathways such as renal and respiratory health. His DXA study was the first to use longitudinal bone scans to predict future diabetes in Qatar.
Research interests
Four to eight research interests as short keywords
Thesis
Longitudinal Analysis of Risk Factors Associated with Diabetes Using Multimodal Data and Machine Learning
Abstract in about 100 words
Supervision: Dr. Zubair Shah
Awards and honours
Awards, scholarships, best-paper prizes and honours with years
Publications with DAQIQ 5
-
Artificial intelligence–based diabetes risk prediction from longitudinal DXA bone measurements
Khan S, Shah Z
Scientific Reports 15: 25706, 2025
Journal articleRead the paper
-
Khan S, Biswas MR, Shah Z
Artificial Intelligence in Healthcare (AIiH 2025), Lecture Notes in Computer Science 16038, Springer, 2025
Conference paperRead the paper Talk and slides
-
Early prediction of type 2 diabetes using multimodal data and tabular transformers
Khan S, Biswas MR, Shah Z
3rd International Conference on Foundation and Large Language Models (FLLM 2025): 592–599, IEEE, 2025
Conference paperRead the paper Free versionTalk and slides
-
Khan S, Shah Z
IEEE International Conference on Information Reuse and Integration for Data Science (IRI 2025): 289–294, 2025
Conference paperRead the paper Conference talk
-
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