How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning
المؤلفون المشاركون
Wan, Ming
Ge, Hui
Fan, Debao
Jin, Lizhu
Du, Xuejie
Yang, Xu
Wang, Xiaofeng
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-12-02
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
Infectious diseases are a major health challenge for the worldwide population.
Since their rapid spread can cause great distress to the real world, in addition to taking appropriate measures to curb the spread of infectious diseases in the event of an outbreak, proper prediction and early warning before the outbreak of the threat of infectious diseases can provide an important basis for early and reasonable response by the government health sector, reduce morbidity and mortality, and greatly reduce national losses.
However, if only traditional medical data is involved, it may be too late or too difficult to implement prediction and early warning of an infectious outbreak.
Recently, medical big data has become a research hotspot and has played an increasingly important role in public health, precision medicine, and disease prediction.
In this paper, we focus on exploring a prediction and early warning method for influenza with the help of medical big data.
It is well known that meteorological conditions have an influence on influenza outbreaks.
So, we try to find a way to determine the early warning threshold value of influenza outbreaks through big data analysis concerning meteorological factors.
Results show that, based on analysis of meteorological conditions combined with influenza outbreak history data, the early warning threshold of influenza outbreaks could be established with reasonable high accuracy.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ge, Hui& Fan, Debao& Wan, Ming& Jin, Lizhu& Wang, Xiaofeng& Du, Xuejie…[et al.]. 2020. How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning. Computational and Mathematical Methods in Medicine،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1139636
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ge, Hui…[et al.]. How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning. Computational and Mathematical Methods in Medicine No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1139636
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ge, Hui& Fan, Debao& Wan, Ming& Jin, Lizhu& Wang, Xiaofeng& Du, Xuejie…[et al.]. How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning. Computational and Mathematical Methods in Medicine. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1139636
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1139636
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر