Interpretation of smartphone-captured radiographs utilizing a deep learning-based approach

In the field of medical imaging, chest radiographs, or X-rays remain as the gold standard for interpreting lung conditions of one and play an important role in clinical care treatment. Recent years witnessed the rising remarkable success of Artificial intelligence (AI) technology in various fields such as computer vision or health services. In detection of diseases in medical images, especially in radiographs, AIbased systems have proven to be powerful tools that can handle medical challenges quickly and cheaply and thereby can significantly improve diagnostics quality and ultimately treat the disease. For examples, detection of skin cancers has been enabled by a vast number of accurate deep learning studies in 2019 such as [1] [2] or [3]. Mammography, which is usually used to detect breast cancer has been the interest of such deep learning studies [4] [5]. A recent advanced study has also been conducted on the use of deep learning to identify Appendicitis using videos that contain CT scans[6]. For radiographs, scientists also applied deep learning to detect particular conditions of lung health, such as pneumonia or consolidation, etc.... Merely, Deep Learning has proven its efficiency in a recent study to generate new synthesis data for training [7]. Some works even lead to the conclusion that AIbased systems can suppress the performance of normal medical doctors or qualified experts in diseases detection [8] [9].