Feature Selection for Disease Prediction in Medical Diagnosis Using Machine Learning

Feature selection is the technique widely used when experimented with huge dataset that can be used for dimensionality reduction to extract most recognizable features from the huge dataset and it also improves the performance of classification methods and helps in selecting relevant features. The most common method utilized in this work to extract the important characteristics from the COVID-19 dataset is feature selection, after which the derived dataset is utilized for disease prediction. The outcomes aim to offer nuanced insights into the applicability of these techniques for disease prediction, aiding healthcare professionals and researchers in selecting suitable models tailored to specific scenarios.