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Tuberculosis detection in chest X-ray using Mayfly-algorithm optimized dual-deep-learning features

What is it about?

This research aims to implement an automated scheme to detect TB infection in chest radiographs (X-ray) using a chosen Deep-Learning (DL) approach. The primary objective of the proposed scheme is to attain better classification accuracy while detecting TB in X-ray images.

Why is it important?

World-Health-Organization (WHO) has listed Tuberculosis (TB) as one among the top 10 reasons for death and an early diagnosis will help to cure the patient by giving suitable treatment. Experimental outcome confirms that the proposed system with DDF yields a classification accuracy of 97.8%using a K Nearest-Neighbor (KNN) classifier.

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Rajakumar M.P.
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