有效利用数据预测 COVID-19 动态:通过机器学习模型进行探索

IF 3.1 Q2 HEALTH CARE SCIENCES & SERVICES
D. Chumachenko, Tetiana Dudkina, Sergiy Yakovlev, T. Chumachenko
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引用次数: 0

摘要

本研究围绕 COVID-19 大流行展开,三年多来,该流行病已成为全球健康问题的焦点。它强调了有效利用流行病模拟模型对有关流行病控制的知情决策的重要性。挑战在于如何恰当地选择、调整和解释这些模型。研究构建了三个统计机器学习模型来预测 COVID-19 在特定地区的传播,并使用真实的 COVID-19 发病率数据对其性能进行了评估。论文对德国、日本、韩国和乌克兰的 COVID-19 发病率和死亡率进行了短期(3、7、14、21 和 30 天)预测。根据所使用的输入数据类型,对每个模型的精确度进行了仔细检查。就各种数据源如何提高预测传染病动态的机器学习模型的解释质量提出了建议。初步研究结果表明,有必要综合利用所有可用数据,在节假日多发期优先使用累积数据,反之则使用每日数据。为尽量减少绝对误差,应使用每日发病率和死亡率编制数据库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effective Utilization of Data for Predicting COVID-19 Dynamics: An Exploration through Machine Learning Models
This study is centered around the COVID-19 pandemic which has posed a global health concern for over three years. It emphasizes the importance of effectively utilizing epidemic simulation models for informed decision-making concerning epidemic control. The challenge lies in appropriately choosing, adapting, and interpreting these models. The research constructs three statistical machine learning models to predict the spread of COVID-19 in specific regions and evaluates their performance using real COVID-19 incidence data. The paper presents short-term (3, 7, 14, 21, and 30 days) forecasts of COVID-19 morbidity and mortality for Germany, Japan, South Korea, and Ukraine. The precision of each model was scrutinized based on the type of input data used. Recommendations are provided on how various data sources can enhance the interpretation quality of machine learning models predicting infectious disease dynamics. The initial findings suggest the need for the comprehensive utilization of all available data, favoring cumulative data during holiday-rich periods and daily data otherwise. To minimize the absolute error, databases should be compiled using daily morbidity and mortality rates.
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来源期刊
CiteScore
6.90
自引率
2.30%
发文量
19
审稿时长
12 weeks
期刊介绍: The overall aim of the International Journal of Telemedicine and Applications is to bring together science and applications of medical practice and medical care at a distance as well as their supporting technologies such as, computing, communications, and networking technologies with emphasis on telemedicine techniques and telemedicine applications. It is directed at practicing engineers, academic researchers, as well as doctors, nurses, etc. Telemedicine is an information technology that enables doctors to perform medical consultations, diagnoses, and treatments, as well as medical education, away from patients. For example, doctors can remotely examine patients via remote viewing monitors and sound devices, and/or sampling physiological data using telecommunication. Telemedicine technology is applied to areas of emergency healthcare, videoconsulting, telecardiology, telepathology, teledermatology, teleophthalmology, teleoncology, telepsychiatry, teledentistry, etc. International Journal of Telemedicine and Applications will highlight the continued growth and new challenges in telemedicine, applications, and their supporting technologies, for both application development and basic research. Papers should emphasize original results or case studies relating to the theory and/or applications of telemedicine. Tutorial papers, especially those emphasizing multidisciplinary views of telemedicine, are also welcome. International Journal of Telemedicine and Applications employs a paperless, electronic submission and evaluation system to promote a rapid turnaround in the peer-review process.
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