Huang, Yi, Song, Insu, Rana, Priyanka, and Koh, Guan (2017) Fast diagnosis of bowel activities. In: Proceedings of the International Joint Conference on Neural Networks. pp. 3042-3049. From: IJCNN 2017: International Joint Conference on Neural Networks, 14-19 May 2017, Anchorage, AK, USA.

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Abstract

Gastrointestinal health conditions, such as diarrhea, are one of the primary reasons of mortality in children as every year almost 1.6 to 2.5 million deaths happen around the world because of it. Diagnosis of gastrointestinal conditions is invasive and expensive to diagnose. We develop a new computerized diagnosis of gastrointestinal health conditions. The method solves the difficulties of recording bowel sounds by using only one bowel sound segment to detect types of bowel activities. The method utilizes Time Series Gaussian Hamming Distance (TSGHD) features to improve the robustness of the classifier in the presence jitters, noises, and location errors. We show that the new method allow recording of bowel sounds more practical and provides clinical explanations of bowel sounds and bowel activities. The proposed approach is evaluated on bowel sounds for classification tasks: normal and abnormal. It shows very promising results: 85.7% of accuracy, 88.5% of sensitivity and 81.3% of specificity.

Item ID:	53171
Item Type:	Conference Item (Research - E1)
ISBN:	978-1-5090-6182-2
Keywords:	biomedical engineering, bio informatics, noise reduction, automated diagnosis, computerized diagnosis
Date Deposited:	16 Jan 2019 01:45
FoR Codes:	46 INFORMATION AND COMPUTING SCIENCES > 4603 Computer vision and multimedia computation > 460308 Pattern recognition @ 100%
SEO Codes:	92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920103 Cardiovascular System and Diseases @ 50% 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920105 Digestive System Disorders @ 50%
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