• Ekta
• Reeta Devi

Chest X-rays (CXRs) are the most commonly performed diagnostic imaging tests worldwide. However, accurately interpreting them requires significant expertise, and misdiagnoses can lead to severe consequences. Computer-Aided Diagnosis (CAD) systems powered by artificial intelligence (AI) and deep learning (DL) have emerged as promising tools to assist radiologists in detecting abnormalities such as pneumonia, tuberculosis, lung nodules, and COVID-19. This paper explores recent advancements in AI-based CXR analysis, discussing key methodologies, challenges, and future directions in CAD for chest radiography.

Artificial Intelligence, Chest X-ray (CXR), Computer-Aided Diagnosis (CAD), Convolutional Neural Networks (CNN), Deep Learning, Medical Imaging.

"Computer-Aided Diagnosis (CAD) for Chest X-Rays Using Artificial Intelligence: An Overview", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 3, page no.g802-g808, March-2022, Available :http://www.jetir.org/papers/JETIR2203704.pdf

"Computer-Aided Diagnosis (CAD) for Chest X-Rays Using Artificial Intelligence: An Overview", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 3, page no. ppg802-g808, March-2022, Available at : http://www.jetir.org/papers/JETIR2203704.pdf