An Efficient and precise medical decision support system using machine learning techniques

Abstract

Data mining in health care is characterized by the extraction or analysis of significant medical trends and knowledge from larger medical datasets. These extracted hidden patterns and information are analyzed to perform effective disease prediction. It was mainly implemented in the healthcare industry to predict the diseases at an earlier stage and helps to improve patient care and reduce costs. It allows the health sector to use the data and analytics extensively thereby recognizing the ineffectiveness. Decision Support Systems usually gather, organize, and analyze a huge amount of information to make a decision and they find a wide range of applications in different fields namely Education, Real estate, healthcare, etc. Decision Support Systems are characterized as collaborative technologies that enable decision-makers to use data and models for problem recognition, problem-solving, and decision-making. They integrate knowledge and models which are meant to support decision-makers. Instead of decision-making, decision support systems have the purpose of maximizing performance. It is necessary to formulate an accurate medical diagnosis in the healthcare sector based on the available medical data which can be done with the aid of the Medical Decision Support System (MDSS). newlineThe MDSS can be defined as a software designed to facilitate clinical decision-making that contrasts the characteristics of a patient with an informatic clinical knowledge base. The patient-specific tests or suggestions are then made available as a preference to the clinician or patient. The knowledgebase, algorithms, and communication mechanisms are the three primary components of an MDSS. newline