Classification of tongue - Glossitis abnormality

A. Rahman, A. Ahmed, Shigang Yue

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)peer-review


This manuscript presents an approach to classify tongue abnormality related to Diabetes Mellitus (DM) following Western Medicine (WM) approach. Glossitis abnormality is one of the common tongue abnormalities that affects patients who suffer from Diabetes Mellitus (DM). The novelty of the proposed approach is attributed to utilising visual signs that appear on tongue due to Glossitis abnormality causes by high blood sugar level in the human body. The 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. 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 abnormality. The visual signs were extracted following a logically formed medical approach, which complies with Western Medicine (WM) approach. Using Random Forest classifier on the extracted visual tongue signs, from 572 tongue samples for 166 patients, the experimental results have shown promising accuracy of 95.8% for Glossitis abnormality.
Original languageUndefined/Unknown
Title of host publicationLecture Notes in Engineering and Computer Science
Publication statusPublished - 7 Jul 2017
EventWorld Congress on Engineering 2017 - Imperial College London, London, United Kingdom
Duration: 5 Jul 20177 Jul 2017


ConferenceWorld Congress on Engineering 2017
Country/TerritoryUnited Kingdom

Research Centres

  • Centre for Intelligent Visual Computing Research

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