Article

Explainability-Driven Tuberculosis Detection: GAN-Augmented CNN–Swin Transformer Hybrid Framework with Signal Processing Insights

2025-12-01

Abstract excerpt

<title>Abstract</title> <p>Globally, tuberculosis (TB) remains a significant health concern, especially in areas with inadequate resources where prompt and precise diagnosis is difficult. The article presents a novel hybrid deep learning architecture that combines Generative Adversarial Networks (GANs), Convolutional Neural Networks (CNNs), and Swin Transformers to answer the demand for reliable and interpretable...

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Literature Corpus work: f76639d6-a7d8-50ad-98f4-7fc74f274fc5
DOI: 10.21203/rs.3.rs-8209065/v1

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