Deep learning methods on chest x-ray radiography for detection and classification of thoracic disease: A survey

Many medical images processing tasks, including chest radiography, have recently been demonstrated to be significantly improved by AI researchers who have used deep learning, particularly CNN. To help radiologists diagnose thoracic disorders, they are required to assist. Determining the presence of one or two thoracic diseases using deep learning models was the driving force behind an effort to construct a real-time, multi-thoracic disease detection and classification model. In this article, we will review breakthrough applications built with deep learning models such as CNNs to detect and classify multiple pathologies in one exam on Chest radiography. Also, we will discuss important design factors and future trends in computer aided diagnosis of multi-disease classification problems in Chest Radiology.