Secure Dengue Epidemic Prediction System: Healthcare Perspective
作者机构：College of Computer Engineering and SciencePrince Sattam bin Abdulaziz University Al-Kharj11942Saudi Arabia
出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)
年 卷 期：2022年第73卷第10期
页 面：1723-1745页
核心收录：
学科分类：1004[医学-公共卫生与预防医学(可授医学、理学学位)] 100401[医学-流行病与卫生统计学] 10[医学]
基 金：The authors extend their appreciation to the Deputyship for Research and Innovation Ministry of Education in Saudi Arabia for supporting this research work through the project number(IF-PSAU-2021/01/17795)
主 题：Internet of things smart air real-time healthcare adaptive neuro-fuzzy inference system
摘 要：Viral diseases transmitted by mosquitoes are emerging public health problems across the *** is considered to be the most significant mosquito-oriented ***,the present study provides an effective architecture for Dengue Virus Infection *** proposed system involves a 4-level architecture for the prediction and prevention of dengue infection *** architectural levels including Dengue Information Acquisition level,Dengue Information Classification level,DengueMining and Extraction level,and Dengue-Prediction and Decision Modeling level enable an individual to periodically monitor his/her probabilistic dengue fever *** prediction process is carried out so that proactive measures are taken *** predictive purposes,probabilistic analysis in terms of Level of Dengue Fever(LoDF)was carried out using the Adaptive NeuroFuzzy Inference *** on the Self-Organized Mapping procedure,the presence of LoDF is *** simulations on datasets of 16 individuals cumulating to 32,255 instances were conducted to test the effectiveness of the presented *** comparison to other decision-modeling methods,significantly improved results in form of classification efficacy,a temporal delay,prediction effectiveness,reliability,and stability were reported for the presented model.
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