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  4. Identifying Medical Terms Related to Specific Diseases
 
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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
DOI
10.1109/ICDMW.2015.71
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.
Unpaywall
URI
https://d8.irins.org/handle/IITG2025/21964
Subjects
Disease Term Classification | Machine Learning | Medical Term Identification | Unified Medical Language System (UMLS)
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