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危机的影响是世界范围的，预测未来变化的可能性和对医疗保健系统的潜在影响的能力很低。使住院系统不堪重负的可能性尤其重要，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、医院入院人数和死亡率，并表示地区、省份和加拿大范围的预测。正在开发基于各种原始数据来源的评估，以估计传染性、分布传播和恢复数据，以更好地了解环境、人们的行为模式和年龄等特征如何影响病例数量的上升和控制。