Analysis the effects of environmental emissions for lung disease detection using ai

Abstract

Recent rapid technological developments make it possible for image analysis algorithms to compete with professionals in terms of accuracy and speed. In recent years, developments in convolutional neural networks and machine learning have improved our ability to categorize and recognize items. There is significant evidence that these models can compete with or surpass experts in challenging tasks such as word processing, image processing, pattern recognition, abstract representation-based decision making, and clinical decision-making. The purpose of this effort is to examine the methods currently used to build machine learning architecture and develop our own model, which will subsequently be used to diagnose lung sickness using digital medical (X-ray) images as accurately as possible. the focus of this research is to identify lung disease using a different type of machine learning methods. newline