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Utilizing high resolution physiological data and artificial intelligence to develop a pediatric cardiac arrest prediction tool for integration into bedside clinical practice

Utilizing high resolution physiological data and artificial intelligence to develop a pediatric cardiac arrest prediction tool for integration into bedside clinical practice
利用高分辨率生理数据和人工智能开发儿科心脏骤停预测工具，以融入床边临床实践
批准号：
396604
负责人：
Laussen Peter C
金额：
$43.48万
依托单位：
Hospital for Sick Children (Toronto)
依托单位国家：
加拿大
项目类别：
Operating Grants
财政年份：
2018
资助国家：
加拿大
项目状态：
已结题
起止时间：
2018-10-01 至 2021-10-01
来源：
https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=396604&lang=en
关键词：
Artificial Intelligence Big Data Bioethics Cardiac Arrest Critical Care Neural Networks Pediatrics Personalized Medicine Prediction

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中文摘要
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英文摘要
Critically ill children are at risk of cardio-pulmonary arrest (CPA). These devastating events occur 300-700 times per year in Canadian pediatric intensive care units (PICUs) and are associated with high mortality (45 to 85%), disability and higher costs
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Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis