A new machine learning approach for prediction of personalized screening time and colorectal polyps recurrence based on genomics, clinical, and imaging data

一种新的机器学习方法，用于根据基因组学、临床和影像数据预测个性化筛查时间和结直肠息肉复发

• 批准号: 568028-2022
• 负责人: Manouchehri, NargesNM
• 金额: $ 3.28万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Postdoctoral Fellowships
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=755627
• 关键词: new; machine; learning; approach; prediction

colorectal cancer, colorectal polyp recurrence, colonoscopy screening, cancer genomics, personalized preventive care, clinical decisions support system, predictive modelling, medical data integration, semi-supervised methods, risk prediction

结直肠癌，结直肠息肉复发，结肠镜检查，癌症基因组学，个性化预防护理，临床决策支持系统，预测模型，医学数据集成，半监督方法，风险预测