Techniques and Approaches for Disease Outbreak Prediction: A Survey

A. Bharambe, D. Kalbande
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引用次数: 7

Abstract

As on today, due to rise in pollution and dense population in India, there has been an increase in health related issues with respect to spreading disease. The recent outbreak of diseases like HINI, dengue, malaria etc. have made people to focus on ways to minimize the effect of infectious disease. This can be achieved if early prediction and detection of such diseases are possible. Research is being carried out in building various prediction models to forecast the outbreak of such epidemics. While the traditional techniques were useful in giving the results, inputs from social media enabled us to detect the presence, prevalence and spread of these disease in a much early manner. Social networking Medias and their blogs have also been used for prediction. To handle such variety and size of data, it is required to design a system using big data approach for forecasting. Big Data is one of the need of the hour area of research that is become increasingly popular in prediction. This paper focuses on the survey carried out on available techniques and presents a unified approach to prepare a conceptual forecasting model.
疾病爆发预测的技术和方法:综述
就像今天一样,由于印度污染加剧和人口密集,与疾病传播有关的健康问题有所增加。最近爆发的HINI、登革热、疟疾等疾病使人们关注如何将传染病的影响降到最低。如果能够及早预测和发现这类疾病,就可以实现这一目标。目前正在研究建立各种预测模型,以预测这类流行病的爆发。虽然传统技术在提供结果方面很有用,但社交媒体的投入使我们能够更早地发现这些疾病的存在、流行和传播。社交网络媒体及其博客也被用于预测。为了处理如此多样和规模的数据,需要设计一个使用大数据方法进行预测的系统。大数据是当前研究领域的需求之一,在预测领域越来越受欢迎。本文重点介绍了对现有技术进行的调查,并提出了一种统一的方法来编制概念预测模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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