A Rough set based Algorithmic Classification of Human Constitution in Major Homoeopathic remedial Classes

Abstract

Among the most crucial and significant aspects of medicine is making accurate newlinediagnoses of disease. If the diagnosis is accurate the medicine can be accurate otherwise newlineit may cause inconvenience to the patients as well as reputation and expertise of the doctor newlinealso can be questionable. Progress of computer science and technology development has newlinea great impact on the field of medicine. newlineThere are various types of medicinal systems. Important among them can be said newlineas Ayurveda, Yoga, Unani, Siddha and Homeopathy. Each Medical system has its own newlinesignificance and a way of treatment .Homeopathy has been chosen for this study. newlineHomeopathy is gaining popularity as a healing technique as well as a medical system. newlineThe base of homeopathy is to study the patient classifies the patient in his relevant group newlineand then further find the remedy; Classification plays an important role here. newlineBased on the literature review it was revealed that homeopathic medical system is newlinebecoming popular medicinal system as it has no or very little side effects. Additionally, newlineit is an atedious approach for accurately classifying patients into their various classes. newlineAdditionally, the most effective method for patient categorization was shown to be Rough newlineSet Theory, a mathematical framework for handling ambiguity, uncertainty, and missing newlinedata. To achieve accuracy, extract data and reduce data Rough Set Theory (RST) is newlineimplemented in this study. Reduct is one of the feature of RST which reduces the no of newlineattributes to be studied in the information table without changing the decision or the end newlineresult. newlineThis study primarily aims to classify patients according to their observable newlinecharacteristics by using RST and expert validation to determine which groups they belong newlineto.In order to achieve this goal, we gathered real-time data from many homoeopaths and newlineorganised it into an appropriate data table.