Creating a Diagnostic Assistance System for Diseases in Kampo Medicine

The aim of this study was to propose a method to assess images of the tongue captured using a polarized light camera for diagnostic use in Kampo medicine. Glossy and non-glossy images of the tongue were captured simultaneously using a polarizing camera and a polarizing plate. Data augmentation was p...

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Autores principales:	Reimei Koike, Keiko Ogawa-Ochiai, Akiko Shirai, Katsumi Hayashi, Junsuke Arimitsu, Hongyang Li, Norimichi Tsumura
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	machine learning Kampo medicine tongue diagnostic assistance Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/4d6671b848534e179fde75e2471325e2
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spelling	oai:doaj.org-article:4d6671b848534e179fde75e2471325e22021-11-11T14:56:39ZCreating a Diagnostic Assistance System for Diseases in Kampo Medicine10.3390/app112197162076-3417https://doaj.org/article/4d6671b848534e179fde75e2471325e22021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/9716https://doaj.org/toc/2076-3417The aim of this study was to propose a method to assess images of the tongue captured using a polarized light camera for diagnostic use in Kampo medicine. Glossy and non-glossy images of the tongue were captured simultaneously using a polarizing camera and a polarizing plate. Data augmentation was performed by modulating the color and gloss, resulting in an increase in the number of images from 11 to 275. To create a data set, the values for which diseases were evaluated by Kampo doctors for all tongue images were taken as the correct values and combined with the features extracted from the tongue images. Using this data set, we constructed a diagnostic support module to evaluate diseases. The resulting mean absolute error of the assessment was 0.44 for qi deficiency, 0.42 for blood deficiency, 0.33 for blood stagnation, 0.36 for yin deficiency, and 0.55 for fluid stagnation, suggesting that the diagnostic assistance module was accurate, and our proposed learning and data augmentation methods were effective.Reimei KoikeKeiko Ogawa-OchiaiAkiko ShiraiKatsumi HayashiJunsuke ArimitsuHongyang LiNorimichi TsumuraMDPI AGarticlemachine learningKampo medicinetonguediagnostic assistanceTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 9716, p 9716 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	machine learning Kampo medicine tongue diagnostic assistance Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	machine learning Kampo medicine tongue diagnostic assistance Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Reimei Koike Keiko Ogawa-Ochiai Akiko Shirai Katsumi Hayashi Junsuke Arimitsu Hongyang Li Norimichi Tsumura Creating a Diagnostic Assistance System for Diseases in Kampo Medicine
description	The aim of this study was to propose a method to assess images of the tongue captured using a polarized light camera for diagnostic use in Kampo medicine. Glossy and non-glossy images of the tongue were captured simultaneously using a polarizing camera and a polarizing plate. Data augmentation was performed by modulating the color and gloss, resulting in an increase in the number of images from 11 to 275. To create a data set, the values for which diseases were evaluated by Kampo doctors for all tongue images were taken as the correct values and combined with the features extracted from the tongue images. Using this data set, we constructed a diagnostic support module to evaluate diseases. The resulting mean absolute error of the assessment was 0.44 for qi deficiency, 0.42 for blood deficiency, 0.33 for blood stagnation, 0.36 for yin deficiency, and 0.55 for fluid stagnation, suggesting that the diagnostic assistance module was accurate, and our proposed learning and data augmentation methods were effective.
format	article
author	Reimei Koike Keiko Ogawa-Ochiai Akiko Shirai Katsumi Hayashi Junsuke Arimitsu Hongyang Li Norimichi Tsumura
author_facet	Reimei Koike Keiko Ogawa-Ochiai Akiko Shirai Katsumi Hayashi Junsuke Arimitsu Hongyang Li Norimichi Tsumura
author_sort	Reimei Koike
title	Creating a Diagnostic Assistance System for Diseases in Kampo Medicine
title_short	Creating a Diagnostic Assistance System for Diseases in Kampo Medicine
title_full	Creating a Diagnostic Assistance System for Diseases in Kampo Medicine
title_fullStr	Creating a Diagnostic Assistance System for Diseases in Kampo Medicine
title_full_unstemmed	Creating a Diagnostic Assistance System for Diseases in Kampo Medicine
title_sort	creating a diagnostic assistance system for diseases in kampo medicine
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/4d6671b848534e179fde75e2471325e2
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Creating a Diagnostic Assistance System for Diseases in Kampo Medicine

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