2 Years Impact Factor:
2.85
5 Years Impact Factor: 1.53
Author: Jagapathi Unnathi, Vojjala Kalyan Prasad, Bollam Stephen, Mr. G Sathish
Abstract:
Tuberculosis (TB) remains a significant public health issue, particularly in India, which accounts for a large proportion of global TB cases. According to the World Health Organization (WHO), India reported over 2.6 million new TB cases annually, with an estimated 440,000 deaths each year. Chest X-ray imaging combined with advanced AI techniques can accelerate TB diagnosis and improve accuracy, making it a promising tool in public health. AI applications help in automating detection, ensuring early intervention, and supporting healthcare workers, especially in resource-limited areas. To leverage deep learning and AI-based approaches for improving the accuracy, speed, and scalability of tuberculosis diagnosis through chest X-ray imaging, thereby supporting India's goal to eliminate TB by 2025. Before the integration of AI, TB diagnosis relied on manual interpretation of chest X-rays by radiologists, sputum smear microscopy, and the Mantoux tuberculin skin test. These meth
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