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A Novel Method of Measuring Pathological Conditions: Using Machine Learning in Tissue Stretch Response Patterns
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- Tagami Yukiho
- Doshisha University
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- Takatori Satoshi
- Doshisha University
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- Mizutani Ken-ichi
- Kobe Gakuin University
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- Kenmotsu Takahiro
- Doshisha University
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- Tsuruyama Tatsuaki
- Kyoto University
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- Ikegawa Masaya
- Doshisha University
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- Yoshikawa Kenichi
- Doshisha University Kyoto University
Bibliographic Information
- Other Title
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- 新規な病態計測法:組織の伸展応答パターンにおける機械学習の活用
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Description
<p>Pathological diagnosis is an important diagnostic technique to determine a medical treatment policy. In the standard method, diagnosis of tissue slices has been investigated based on the visual inspection by microscope. However, it is difficult to evaluate a state of disease in a quantitative manner using the current methodology. Here, we propose a novel pathological diagnosis method focusing on the physical characteristics of tissue sections depending on the difference of disease state. We have found that the cracking pattern caused by applying tension to tissue sections depends on the pathological condition. By adapting such cracking pattern as a quantitative index for pathological diagnosis, it becomes possible to perform pathological diagnosis in a reliable and quantitative manner.</p>
Journal
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- Transaction of the Japan Society for Simulation Technology
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Transaction of the Japan Society for Simulation Technology 14 (2), 133-137, 2022
Japan Society for Simulation Technology
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Details 詳細情報について
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- CRID
- 1390857757567142144
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- ISSN
- 18835058
- 18835031
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- Text Lang
- ja
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- Article Type
- journal article
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- Data Source
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- JaLC
- KAKEN
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- Abstract License Flag
- Disallowed