Abstract
Diseases of the lung, such as pneumonia, tuberculosis, and lung cancer, are common, and the medical records keep increasing. This demands the development of a method that will accurately detect all known diseases. Traditional diagnostic techniques involving X-rays and computer tomography scans require expert interpretation and may be time-consuming with a possibility of human error. The paper discusses the application of machine learning models in the detection of lung diseases, especially those that use the deep learning technique with convolutional neural networks. It also describes the review of related works, methodologies applied, the presentation of results, and discussions of implications for future work in improving diagnostic accuracy. for future work in improving diagnostic accuracy.