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Author

Mehmet Zahid Genç

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Open access Oct 2026

MEE-Net: a lightweight CNN with interpretability assessment for cardiomegaly detection from chest X-rays on edge devices

Cardiomegaly is a clinically important indicator of cardiovascular risk, yet its detection from chest radiographs remains challenging due to inter-observer variability and the limited deployability of current deep learning models in resource-constrained settings. To address these limitations, we propose MEE-Net (Me...

Yaser Dalveren, Mehmet Zahid Genç, Ali Kara et al. · 0 citations
Open access Dec 2025

Automated skeletal maturity staging from hand-wrist radiographs using deep learning models: A decision support system based on Fishman’s indicators

Objective This study aimed to develop an automated system for skeletal maturity staging using deep learning (DL) models of hand-wrist radiographs based on Fishman’s method. Methods In total, 2,318 hand-wrist radiographs of patients aged 8–19 years were retrospectively analyzed. Each radiograph was labeled by experts ac...

Yeşim S. Kaya, Berrin Çelik, Mehmet Zahid Genç et al. · 0 citations

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