After KAUST Academy
Samaher joined the Data Science Program run by Saudi Digital Academy and WeCloudData. Samaher was named Champion of the Week in September 2026 and shared the final project, MADAD, an AI-driven system for hospital inventory and supply sharing, in October.
Summer project
Artificial Intelligence Specialization · Cohort 2026
Explainable Knowledge Distillation for Bone Fracture Classification Using X-ray Images
Bone fracture classification from X-ray images is an important application of deep learning for supporting clinical diagnosis. However, high-capacity models are often computationallyexpensiveanddifficulttointerpret,limitingtheirdeploymentinresource- constrained healthcare environments. This study investigates an Explainable Knowledge Distillation(EKD)frameworkthatcombinesprediction-basedknowledgedistillationwith class-discriminative attention transfer to develop a lightweight and interpretable fracture classifier. Using the FracAtlas dataset, EfficientNet-B6 was selected and optimized as the teacher model, while MobileNetV2 was selected as the lightweight student. The EKD student was evaluatedunder three training settings: No Augmentation, RandAugment, and AugMix, and compared with the corresponding MobileNetV2 baselines. EKD improvedvalidationaccuracyacrossallthreesettings,withAugMixachievingthehighest validationaccuracyof0.8742. Qualitativecomparisonsofteacherandstudentattention maps showed partial spatial correspondence,althoughthe student maps were generally broaderandmorediffuse. Overall,theresultsdemonstratethepotentialofexplainability- guided knowledge distillation for improving lightweight fracture classification while encouraging similarity between teacher andstudent attention patterns.
With KAUST Academy
- Cohort 2026
Artificial Intelligence Specialization
King Khalid University · Artificial Intelligence Summer School
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