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A Study on Dengue Fever in Bangladesh: Predicting the Probability of Dengue Infection with External Behavior with Machine Learning

机译：孟加拉国登革热的研究：预测机器学习外部行为的登革热感染概率

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The “2019 Dengue Outbreak” was a nationwide pandemic situation in Bangladesh, particularly in Dhaka city. About 179 people died and 101,354 confirmed dengue cases were found all over the country. The developing countries like Bangladesh have some limitations in the medical sector and many people don't get proper treatment in time. Henceforth, this research work has attempted to predict the chances to get infected with dengue fever from some external behaviors, like-fever, pain, sitophobia, headache etc. This article has demonstrated a model to predict the probability of dengue fever before taking the pathological test. So, the suspective patient may get some initial diagnosis by giving their anatomical symptoms as input and further this will decrease the dependency on the pathological test for acquiring the primary treatment. Different machine learning models are used to predict the probability and an accuracy near to 100% has been achieved finally.
机译：“2019年登革热爆发”是孟加拉国的全国性流行形势，特别是在达卡市。 大约179人死亡，101,354人在全国范围内发现了101,354名证明案件。 像孟加拉国这样的发展中国家在医疗领域有一些局限性，许多人不会及时获得适当的治疗。 从此，这项研究工作已经试图预测从一些外部行为感染登革热的机会，如发烧，疼痛，终原，头痛等。本文已经证明了一种模型，以预测登革热之前的概率 测试。 因此，疑似患者可以通过将其解剖症状作为输入提供一些初始诊断，并进一步这将降低对获取初级治疗的病理试验的依赖性。 不同的机器学习模型用于预测最终达到100％近100％的概率。

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