A Multi-Stage Deep Learning Approach to Tuberculosis Detection with Explainable Insights
Published in Accepted at the 2nd International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM 2025), DUET, Gazipur, Bangladesh, 2025
Accepted at NCIM 2025, this work proposes a multi-stage deep learning pipeline for automated tuberculosis detection, integrating explainable AI to enhance clinical trust.
Recommended citation: Shadman Sobhan, Abduz Zami, Mohiuddin Ahmed, Tanvir Mahtab Zihan, Tanvir Ahmed Khan, Aranya Saha. (2025). A Multi-Stage Deep Learning Approach to Tuberculosis Detection with Explainable Insights. Accepted at NCIM 2025.
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