| Project/Area Number |
25K15935
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 90130:Medical systems-related
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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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| Co-Investigator(Kenkyū-buntansha) |
管野 貴浩 島根大学, 学術研究院医学・看護学系, 教授 (60633360)
BommeGowda SiddabasaveGowda 北海道大学, 保健科学研究院, 准教授 (50800504)
山本 達之 島根大学, 学術研究院農生命科学系, 教授 (60230570)
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| Project Period (FY) |
2025-04-01 – 2028-03-31
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| Project Status |
Granted (Fiscal Year 2025)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2027: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2026: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2025: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
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| Keywords | Raman spectroscopy / oral cancer / saliva / diagnosis / machine learning |
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| Outline of Research at the Start |
Oral cancer is rising in low- and middle-income countries, with over 80% of cases diagnosed late, leading to a 5-year survival rate of only ~25%. Early detection enables effective, low-cost treatment, but access to advanced screening is limited. This study proposes a portable, non-invasive method using AI-assisted Raman spectroscopy of saliva for early diagnosis. The label-free technique provides rapid, reliable results via a laptop, enabling onsite use. This approach aims to improve survival and support point-of-care diagnostics in underserved regions.
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