Machine Learning Approach for Personalized Prediction of Renal Graft Survival

Research Project

Project/Area Number	23K17002
Research Category	Grant-in-Aid for Early-Career Scientists
Allocation Type	Multi-year Fund
Review Section	Basic Section 62010:Life, health and medical informatics-related
Research Institution	Shonan Kamakura General Hospital, Medical Corporation Tokushukai (Center for Clinical and
Principal Investigator	Salybekov Amankeldi 医療法人徳洲会湘南鎌倉総合病院(臨床研究センター), 湘南先端医学研究所再生医療開発研究部, 主席研究員 (80850776)
Project Period (FY)	2023-04-01 – 2025-03-31
Project Status	Granted (Fiscal Year 2023)
Budget Amount *help	¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000) Fiscal Year 2024: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000) Fiscal Year 2023: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Keywords	Kidney / Transplantation
Outline of Research at the Start	1) Data preprocessing 2) Phenotype data normalization (histology, laboratory, and clinical variables) 3) Missing data imputation and synthetic data generation 4) Model development ( random forest, LGBM, XgBoost, SVM etc. Important features development. 5) Validation of the dataset and deployment of final model