Using AI to predict COVID19 impacts on Canada's health system

使用人工智能预测新冠肺炎 (COVID19) 对加拿大卫生系统的影响

• 批准号: 549866-2020
• 负责人: McBean, Edward
• 金额: $ 3.64万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=701242
• 关键词: Using; AI; predict; COVID19; impacts

The impact of the COVID19 crisis is at world scale, with minimal ability to predict the potential for future changes, and the potential impacts for the healthcare system. The potential to overwhelm the hospitalization system is of particular importance as there has to be forecasting models to improve understanding of the short-term future. This research will be accomplished using the power of Artificial Intelligence (AI) models for prediction of 'confirmations' of COVID19, hospital entries, and death rates, with representations for regions, provinces and Canada-wide projections. Assessments based upon various raw data sources are being developed to estimate the infectivity rates, the distribution spread and the recovery data, to improve understanding of how such features as the environment, and people's behavioral patterns and age, influence the escalation and control of case loads.

COVID19危机的影响是世界规模，预测未来变化的潜力以及对医疗保健系统的潜在影响的能力最低。 不堪重负的住院系统的潜力尤其重要，因为必须有预测模型来提高对短期未来的了解。 这项研究将使用人工智能（AI）模型的力量来预测Covid19的“确认”，医院参赛和死亡率，以及各地区，省份和加拿大范围内的预测。 正在开发基于各种原始数据源的评估，以估计感染率，分布扩散和恢复数据，以提高人们对环境以及人们的行为模式和年龄的理解，影响案件负荷的升级和控制。