Classification of Tongue - Glossitis Abnormality

Rahman, Ashiqur and Ahmed, Amr and Yue, Shigang (2017) Classification of Tongue - Glossitis Abnormality. Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering . pp. 1-4. ISSN 2078-0958

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Abstract

Glossitis abnormality is a tongue abnormality affecting patients suffering from Diabetes Mellitus (DM). The novelty of the proposed approach is attributed to utilising visual signs that appear on the tongue due to Glossitis abnormality caused by the high blood sugar level in the human body. The clinical test for the blood sugar level is inconvenient for some patients in rural and poor areas where medical services are minimal or may not be available at all.

This paper presents an approach to classifying a tongue abnormality related to Diabetes Mellitus (DM) following Western Medicine. To screen and monitor human organ effectively, the proposed computer-aided model predicts and classifies abnormality appears on the tongue or tongue surface using visual signs caused by the Glossitis abnormality. The visual signs extracted following a coherent diagnosis procedure complying with Western Medicine (WM) in practice. The experimental result has shown a promising accuracy of 95.8% for the Glossitis abnormality by applying Random Forest classifier on the extracted visual signs from 572 tongue samples of 166 patients.

Keywords:Tongue Classification, Random Forest, Machine Learning, Western Medicine
Subjects:G Mathematical and Computer Sciences > G760 Machine Learning
G Mathematical and Computer Sciences > G400 Computer Science
G Mathematical and Computer Sciences > G720 Knowledge Representation
Divisions:College of Science > School of Computer Science
ID Code:35378
Deposited On:02 Dec 2019 10:00

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