Paper Key : IRJ************133
Author: Harshdeep C. Kedare,Nilesh R. Wankhade,Shravani S. Raut,Ankita A. Pachorkar,Chetana S. Desale
Date Published: 03 May 2024
Abstract
In the ongoing battle against Tuberculosis (TB), a significant global health challenge, this project harnesses the capabilities of machine learning and advanced imaging to revolutionize the diagnosis of Pulmonary Tuberculosis. TB remains a major cause of mortality in Low and Middle-Income Countries (LMICS), where deficiencies in healthcare infrastructure and limited local medical expertise have impeded accurate diagnosis and timely intervention. The key challenge addressed by this research is the development of an efficient and reliable diagnostic system for TB, particularly for remote or resource-poor settings. Traditional diagnostic methods often fall short, leading to delayed treatment and unfavorable patient outcomes. To overcome these limitations, this study explores the potential of machine learning, focusing on Convolutional Neural Networks (CNN) and advanced image processing.