Diagnosis Support System for General Diseases by implementing a Novel Machine Learning based Classifier

Abstract

Millions of folks around the earth are affliction from late disease identification and diagnosis. An incredible amount of health information has been obtained by the latest technologies in digital medical services and information communication technologies. Disease diagnosis and artificially intelligent decision support systems have drawn tremendous attention from many scientists and research community worldwide. Various algorithms developed and applied with the aid of machine learning techniques that can substantially lead to the resolution of the system of health care and can help personnel involved in the early diagnosis of diseases. This research paper will propose an artificial intelligent algorithm which helps us to effectively, rapidly and accurately classify the information. The Proposed Disease Diagnosis Support Systems (DDSS) can assist clinicians to monitor the information, facilitate their evaluation by means of a preparatory treatment and decrease evaluation time per patient. The patients may inevitably be notified and recommended dietary suggestions also. This system will allow clinicians to focus on attending patients in accordance with their homeostasis. It decreases the volume of work of doctors and enables them to define patients who need to be examined more urgently or meticulously. Even with the widespread growth of such systems security of digital data and its privacy is still a major challenge yet to solve.