Comparative Analysis of Machine Learning and Optimization Techniques in Chest X-ray Image Analysis for Medical Diagnosis

Nowadays, pneumonia, lung cancer, and COVID-19 are the main causes of death, particularly in developing nations. Even if far less advanced instruments and therapies are used to identify and cure illness. The detection of these diseases remains a main alarm in developing nations. This paper offers multiple disease detection by using optimized machine learning methods and a heuristic algorithm. Various complications and characteristics are also described for the disease. The proposed methodology positively described various machine learning methods such as KNN, support vector machine (SVM), Logistic Regression (LR), Random Forest (RF), and RBM, etc. It also includes adaptive and altruistic PSO (AAPSO) and heuristic red fox optimization (HRFO) methods for the classification and optimization process of pneumonia, Covid-19, and lung cancer. The overall analysis of this methodology, the adaptive and altruistic PSO method reached better performance as compared to other methods