Disease analysis using machine learning approaches in healthcare system

摘要

Abstract This paper addresses disease analysis using machine learning approaches in healthcare system. Several approaches have been used to identify various disease as their corresponding model, but generic model for detecting disease is a challenging task. Thus, this paper proposed the model for disease detection using machine learning approaches with various methodologies such as support vector machine (SVM), K-nearest neighbours, random forests, artificial neural networks (ANNs), and logistic regression. This paper is also used an evaluation matrix with different parameters for performance analysis. The experimental performance is identified as per proposed model through the evaluation matrix. The outcomes disclose that the ANNs method performed good compare to others based on accuracy (97.94), precision (96.78), and F1-score (97.87), respectively. The correlation approach also determined the number of attributes with very close diagonal values i.e., 100. The comparative approaches are strongly analysed in experiments for clarity of performance.