The Development of Machine Learning Algorithms to Identify Perioperative Adverse Events Using Real-world Data

使用真实数据识别围手术期不良事件的机器学习算法的开发

• 批准号: 471987
• 负责人: Wu Guosong
• 金额: $ 6.56万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Fellowship Programs
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-10-01 至 2024-10-01
• 项目状态: 已结题
• 来源: https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=471987&lang=en
• 关键词: Care Quality; Patient Safety

In Canada, one in ten patients experiences adverse events (AEs) during hospitalization. Over half of AEs are related to surgery. The economic burden of hospital AEs were estimated to be 1.1 billion dollars in Canada, importantly, most of AEs are preventab

在加拿大，十分之一的患者在住院期间发生不良事件（AE）。超过一半的AE与手术相关。在加拿大，医院AE的经济负担估计为11亿美元，重要的是，大多数AE是可以预防的。