IJAIEM

G. Uma naga malleshwari , M. Deeksha Reddy , R.Srujan Reddy , T.Bhargavi

Abstract

Tuberculosis (TB) is an infectious disease primarily caused by Mycobacterium tuberculosis, mainly affecting the lungs but potentially spreading to other organs like the brain, kidneys, or spine. It spreads through microscopic droplets released when an infected person coughs, sneezes, or talks. In 2021, the World Health Organization estimated that 10.6 million people worldwide were affected by TB, with 1.6 million deaths. Notably, TB cases increased by 3.6% between 2020 and 2021. When TB bacteria enter the respiratory system, immune cells called macrophages attempt to engulf them, but the bacteria c an survive and form granulomas—dense clusters of immune cells and bacteria. Early detection, prognosis, and identification of resistant TB cases are crucial.The objective of this work is to use deep learning Convolutional Neural Network (CNN) to predict drug resistance and drug sensitivity in tuberculosis based on the genomic data. The existing techniques for determining drug resistan