LITERATURE REVIEW: LUNG DISEASE DETECTION BASED ON X-RAY USING ARTIFICIAL INTELLIGENCE

Abstract

According to a WHO survey in 2019, 4 of the 10 most common diseases that kill people are lung disease. Lung disease is a significant problem for all of us, but until now there has not been found an effective drug to detect it earlier, so that in general lung disease is diagnosed in a severe condition. One example of a lung disease taken as a sample is pneumonia. This research aims to develop a method that is faster and more accurate in detecting individuals infected with pneumonia by using Artificial Intelligence, especially by using Convolutional Neural Network (CNN) architecture in its learning. The research method used in this study is literature review, in which related articles are collected and processed using the Mendeley application. The criteria used in the selection of articles were articles published in 2020 which discussed the use of Artificial Intelligence in treating pneumonia. Based on the collection and discussion of several existing studies, it can be concluded that by using an Artificial Intelligence system, pneumonia detection in individuals can be carried out through pattern analysis on Lung X-ray results with a high degree of accuracy, using existing training data