Data Classification Techniques for Disease Symptoms Detection: A Systematic Literature Review

Abstract

Data classification techniques are very useful for disease symptoms detection. Doctor and medical personnel need a software that can help treat patients. When developing software for diagnose disease, it must choose data classification techniques based on disease that will be diagnose. The failure of choose data classification techniques, it may disease diagnose inaccurately. Software developer team must know data classification techniques for disease symptoms detection. With data classification techniques, it can ease doctor and medical personnel in disease diagnosis. There are some factors that affect to choose the best data classification method based on disease diagnose are information, detection, prevention, and management of disease including fraud in health insurance. It must find the best data classification techniques when they develop an application for diagnose disease. Data classification techniques must have intense of usefulness and analyze data accurately. The aim of this paper to review data classification techniques, data classification techniques process run, the used of data classification and factors that influencing when choose data classification techniques based on disease. This paper will give benefits to doctor and medical personnel and software developer team to understand about data classification techniques for disease diagnosis and also they can build an application that can detect disease accurately. The content of this paper are data classification definition, data classification run process and data classification usability.