Application of artificial intelligence in digital chest radiography diagnosis of pneumoconiosis

Abstract

Pneumoconiosis is the occupational disease with the highest burden in China currently. The diagnosis of pneumoconiosis mainly relies on manual reading of X-ray high-kilovoltage or digital photography chest radiograph, which has some problems such as low efficiency, strong subjectivity, and cannot accurately judge the critical lesions. With the progress of machine-aided diagnosis technology, the efficient, objective and quantitative of artificial intelligence diagnosis technology just solve the shortcomings above. This paper reviews the research progress in digital chest radiography diagnosis of pneumoconiosis using artificial intelligence technology, especially deep learning model, combined with the limitations of conventional manual reading, in order to clarify the application prospect of artificial intelligence technology in the diagnosis of pneumoconiosis by digital chest radiography, and provide a direction for future research in this field.