Efficient estimation in a novel hybrid model combining deep learning and joint modeling of longitudinal and time-to-event analysis for multimodal health data

结合深度学习和多模态健康数据纵向和事件时间分析联合建模的新型混合模型的有效估计

• 批准号: 559863-2021
• 负责人: LAC, LEAN
• 金额: $ 2.55万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Alexander Graham Bell Canada Graduate Scholarships - Doctoral
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=723733
• 关键词: Efficient; estimation; novel; hybrid; model

statistical joint models, deep learning models, novel hybrid models, efficient estimators, longitudinal and time-to-event, electornic health records, mammograms, open source software tool, data science, risk prediction

统计联合模型，深度学习模型，新型混合模型，高效估计器，纵向和事件时间，电子健康记录，乳房X光检查，开放源码软件工具，数据科学，风险预测