Identifying Medical Terms Related to Specific Diseases
Source
Proceedings 15th IEEE International Conference on Data Mining Workshop Icdmw 2015
Date Issued
2016-01-29
Author(s)
Shekhar, Mihir
Chikka, Veera Raghavendra
Thomas, Lini
Mandhan, Sunil
Karlapalem, Kamalakar
Abstract
We present an automated disease term classification model using machine learning techniques that classifies a medical term to a specific disease class. We work on five particular diseases: Cancer, AIDS, Arthritis, Diabetes and heart related ailments. We identify and classify medical terms like drug names, symptoms, abbreviations, disease names, tests, etc., into their specific diseases classes. The results illustrate that our model for disease term classification finds all disease term classes with an average F-score of 0.966.
Subjects
Disease Term Classification | Machine Learning | Medical Term Identification | Unified Medical Language System (UMLS)
