Computer-Aided Diagnosis using Machine Learning Techniques

Abstract

Computer-aided diagnosis (CAD), a field of medical analysis, is rapidly advancing in a large range and is becoming more complex. Computer-aided recently, there has been a lot of interest in diagnostics for the reason inaccurate medical diagnosis could result in significantly misleading therapies. Machine learning (ML) is a key component of computer-aided diagnostic examinations. A simple equation cannot identify an organ in the body with the required accuracy. Therefore, pattern recognition requires learning from examples. Using pattern detection techniques and machine learning (ML) techniques, it is possible to improve the accuracy of diagnosing diseases and making appropriate treatment decisions in the medical field It is important to them that decisions are made objectively. Machine Learning (ML) provides a reliable approach to the development of improved, automated algorithms for the analysis of high- dimensional, multi-modal biological data. This survey article compares various machine learning approaches and algorithms for a variety of diseases' detection. The range of Machine Learning (ML) methods and methods utilized in the medical diagnosis and decision- making are analyzed