Analyze and Detect Lung Disorders Using Machine Learning Approaches—A Systematic Review

The lung is a decisive organ for the human body’s functioning. If there is any problem with the functioning of the lungs, it is called a lung disorder. To reduce the risk factors and maintain healthy lungs, prevent this as early as possible. From 2019 onwards, due to COVID-19, so many people have been infected with lung disorders because the coronavirus affects the lungs. Lung disorders spread throughout the respiratory system gradually, so the initial prevention stage will help to achieve the best results. The increasing rate of lung disorders causes a growth in the death rate and requires pricey medicinal treatment. Because of the significance of these issues, researchers have implemented a variety of methods to detect lung disorders. This paper considered a detailed systematic review of AI methods for the early discovery of lung disorders. The key advantage of AI lies in its ability to autonomously learn, extract, and interpret features from diverse datasets like images, text, and videos, eliminating the need for conventional manual coding or rule-based approaches. The aim of the article is to provide a survey on deep learning–based techniques and available datasets to detect lung disorders, and we proposed a methodology that can detect the disease of lung as untimely as possible, which will assist the doctors to save the patient’s life.