NOVEL HYBRID ARTIFICIAL INTELLIGENCE-BASED ALGORITHM TO DETERMINE THE EFFECTS OF AIR POLLUTION ON HUMAN ELECTROENCEPHALOGRAM SIGNALS

摘要

Air pollution is a serious global issue. The complicated mix of gases, fluids, and particle matter, heterogeneous, and growing pollutants from cars, manufacturers, or houses, damage the ionosphere and also damage human health. In preliminary research, the risk for short and long-term exposure to coronary heart disease in existing levels of ambient particulate matter was consistently raised. These challenges can be modelled with Artificial intelligence (AI). Their benefit is that they can resolve the issue without the realisation of the conceptual link between the input and output data under the situations of partial data. The AI approach may be used to accurately identify coronary disease, and numerous diseases to prevent heart problems. This paper provides a comprehensive analysis of the data on air pollution and cardiovascular disease by healthcare experts and regulatory authorities and also differentiates individuals with cardiovascular disease from healthy individuals easily. The decision support system focused on AI Technology can help physicians better diagnose heart patients. When chosen by the Correlation-based function subset selection algorithm, the classifier logistic regression for 20-fold cross-validation exhibited the greatest 92% accuracy.