A Comprehensive Survey of Machine Learning Algorithms for Multi-Disease Prognosis

Abstract

In this comprehensive analysis, study of various machine learning-based systems for multi-disease prognosis has been conducted. Predictive machine learning algorithms are used extensively in the domain of medical science thereby leading to a considerable improvement in accurately predicting a disease. The timely identification and accurate measurements of these conditions hold the potential for a methodical and efficacious treatment. As research solidifies, the possibilities of computing methods to both optimize and enhance comparative systems seems vast. This comprehensive review aims at providing an intricate and highly detailed analysis of numerous machine learning algorithms and the functioning working environment specifically focused on prognosis of diseases such as myocardial infarction, diabetes and chronic kidney disease. The study thus offers an amalgamation of the most recent medical surveys, thereby contributing to the ongoing research in the field of medical science.