Heterogeneity-Aware, Cross-Domain Feature-Aligned Genetic Diagnosis System for Malignant Gliomas

• Project/Area Number: 25K21579
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 90130:Medical systems-related
• Research Institution: Tohoku University
• Principal Investigator: Zeng Yuwen 東北大学, 総合知インフォマティクス研究センター, 助教 (80994813)
• Project Period (FY): 2025-04-01 – 2028-03-31
• Project Status: Granted (Fiscal Year 2025)
• Budget Amount: ¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000); Fiscal Year 2027: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000); Fiscal Year 2026: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000); Fiscal Year 2025: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
• Keywords: Glioma genetic diagnosis / Computer-aided diagnosis / Trustworthy AI

Outline of Research at the Start

This research is positioned to develop clinically acceptable diagnostic tools for genetic alterations in malignant gliomas and to bridge imaging and histological analysis through AI for genetic diagnosis, meeting the growing demand for personalized medicine and advanceing precision medicine.