2022 Fiscal Year Annual Research Report
Development of artificial intelligence assisted Raman microscopy for reliable and automated examination of urine sediment
| Project/Area Number |
21K18081
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| Research Institution | Shimane University |
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Principal Investigator |
H Noothalapati 島根大学, 学術研究院農生命科学系, 助教 (30748025)
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| Project Period (FY) |
2021-04-01 – 2023-03-31
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| Keywords | Raman spectroscopy / Urinalysis / Urine sediment analysis / Artificial intelligence / disease diagnosis / machine learning / MCR-ALS / multivariate analysis |
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| Outline of Annual Research Achievements |
Urine sediment microscopy is vital in accurate diagnosis of kidney and urinary tract diseases. However, it is not universally adopted because it expensive, time consuming and required trained personnel. So, we plan to develop artificial intelligence (AI) assisted Raman microscopy for reliable and automated examination of urine sediment. We prepared artificial urine and measured Raman spectra of various components in urine successfully. We then employed multivariate analyses such as principal component analysis (PCA) to differentiate multiple components but it did not provide detailed molecular information. Therefore we further employed multivariate curve resolution analysis (MCR) to extract pure molecular spectra which helped to identify markers for objectively diagnosis.
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Research Products
(11 results)
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[Journal Article] Development of in-situ Raman diagnosis technique of eosinophil esophagitis2023
Author(s)
Zakaria Riki、Andriana Bibin. B.、Watanabe Takumu、Maryani Anisa、Paramitha Pradjna N.、Kuntana Yasmi P.、Kusaka Yukako、Noothalapati Hemanth、Iwasaki Keita、Oshima Naoki、Hashimoto Kosuke、Matsuyoshi Hiroko、Ishihara Shunji、Yamamoto Tatsuyuki、Sato Hidetoshi
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Journal Title
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
Volume: 285
Pages: 121804～121804
DOI
Peer Reviewed / Int'l Joint Research
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