Self Health Diagnosis System for Korean Traditional Medicine with Enhanced ART2

Abstract

In this paper, we propose a self health diagnosis system based on Korea Traditional Medicine that has thousand years of history and popular in Korean general public. The system requires constructing a reliable diseasessymptoms database and classification/learning method. After constructing database based on various government reports and Engel Pharm with 60 diseases, 161 representative symptoms, an enhanced ART2 algorithm extracts top five most probable diseases generated by simple user input. The constructed database and test diagnosis results are verified by Korean Traditional medical doctors and verified as reliable in accuracy.