目的/意义系统梳理基于互联网数据的传染病预测模型相关研究,助力实现传染病监测关口前移,为构建传染病智慧化立体防治体系提供参考。方法/过程对Web of Science核心数据库和中国知网收录的近20年基于互联网数据的传染病监测预警研究发...目的/意义系统梳理基于互联网数据的传染病预测模型相关研究,助力实现传染病监测关口前移,为构建传染病智慧化立体防治体系提供参考。方法/过程对Web of Science核心数据库和中国知网收录的近20年基于互联网数据的传染病监测预警研究发展历程及研究方向进行梳理,分析当前主要问题与挑战,总结常见预测模型及其优化方向。结果/结论互联网传染病监测研究呈监测疾病多样化、数据来源精细化和专业化等趋势。由于互联网数据的复杂性和不确定性,现有模型大多仅适用于短时或实时预测。通过构建组合模型、加强多源数据融合、完善关键词与影响因素选择等方式,可进一步优化模型,加强拟合效果和预测能力。展开更多
Faced with the current time-sensitive COVID-19 pandemic,the overburdened healthcare systems have resulted in a strong demand to develop newer methods to control the spread of the pandemic.Big data and artificial intel...Faced with the current time-sensitive COVID-19 pandemic,the overburdened healthcare systems have resulted in a strong demand to develop newer methods to control the spread of the pandemic.Big data and artificial intelligence(AI)have been leveraged amid the COVID-19 pandemic;however,little is known about their use for supporting public health efforts.In epidemic surveillance and containment,efforts are needed to treat critical patients,track and manage the health status of residents,isolate suspected cases,and develop vaccines and antiviral drugs.The applications of emerging practices of artificial intelligence and big data have become powerful"weapons"to fight against the pandemic and provide strong support in pandemic prevention and control,such as early warning,analysis and judgment,interruption and intervention of epidemic,to achieve goals of early detection,early report,early diagnosis,early isolation and early treatment.These are the decisive factors to control the spread of the epidemic and reduce the mortality.This paper systematically summarized the application of big data and AI in epidemic,and describes practical cases and challenges with emphasis on epidemic prevention and control.The included studies showed that big data and AI have the potential strength to fight against COVID-19.However,many of the proposed methods are not yet widely accepted.Thus,the most rewarding research would be on methods that promise value beyond COVID-19.More efforts are needed for developing standardized reporting protocols or guidelines for practice.展开更多
文摘目的/意义系统梳理基于互联网数据的传染病预测模型相关研究,助力实现传染病监测关口前移,为构建传染病智慧化立体防治体系提供参考。方法/过程对Web of Science核心数据库和中国知网收录的近20年基于互联网数据的传染病监测预警研究发展历程及研究方向进行梳理,分析当前主要问题与挑战,总结常见预测模型及其优化方向。结果/结论互联网传染病监测研究呈监测疾病多样化、数据来源精细化和专业化等趋势。由于互联网数据的复杂性和不确定性,现有模型大多仅适用于短时或实时预测。通过构建组合模型、加强多源数据融合、完善关键词与影响因素选择等方式,可进一步优化模型,加强拟合效果和预测能力。
基金the National Key R&D Program of China(Grant No.2021ZD01144101).
文摘Faced with the current time-sensitive COVID-19 pandemic,the overburdened healthcare systems have resulted in a strong demand to develop newer methods to control the spread of the pandemic.Big data and artificial intelligence(AI)have been leveraged amid the COVID-19 pandemic;however,little is known about their use for supporting public health efforts.In epidemic surveillance and containment,efforts are needed to treat critical patients,track and manage the health status of residents,isolate suspected cases,and develop vaccines and antiviral drugs.The applications of emerging practices of artificial intelligence and big data have become powerful"weapons"to fight against the pandemic and provide strong support in pandemic prevention and control,such as early warning,analysis and judgment,interruption and intervention of epidemic,to achieve goals of early detection,early report,early diagnosis,early isolation and early treatment.These are the decisive factors to control the spread of the epidemic and reduce the mortality.This paper systematically summarized the application of big data and AI in epidemic,and describes practical cases and challenges with emphasis on epidemic prevention and control.The included studies showed that big data and AI have the potential strength to fight against COVID-19.However,many of the proposed methods are not yet widely accepted.Thus,the most rewarding research would be on methods that promise value beyond COVID-19.More efforts are needed for developing standardized reporting protocols or guidelines for practice.
