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A predictive model for the effective prognosis of Asthma using Asthma severity indicators

机译：使用哮喘严重程度指标的哮喘有效预后预测模型

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摘要

The work presented in the paper discusses the implementation of a predictive model for the effective prognosis of Asthma using Asthma Severity indicators. The model utilizes the survey data that was recorded by the University of Innsbruck, Austria, collected during a study that was related to lung operation and diseases of the respiratory tracts. The model performs feature transformation and feature selection to identify significance of Asthma indicators which shall be treated as Asthma severity indicators. The dataset is pre-processed by standardizing data using normalizing techniques. The impact of pre-processing is verified by performing prediction of likely outcome of Asthma in subjects with the identified severity indicators. The Predictive performance of the model is analyzed by applying KNN classifier and Support Vector Machine techniques which yield considerably good results in terms of performance metrics like Precision, Recall and F-Measure.
机译：本文介绍的工作讨论了使用哮喘严重程度指标的有效预后的预测模型的实施。该模型利用奥地利因斯布鲁克大学记录的调查数据，在一项与肺部经营和呼吸道疾病有关的研究中收集。该模型进行特征转化和特征选择，以鉴定哮喘指标的重要性，该指标应被视为哮喘严重程度指标。数据集通过使用归一化技术标准化数据来预处理。通过在受试者中对鉴定的严重性指标进行可能的哮喘结果预测来验证预处理的影响。通过应用KNN分类器和支持向量机技术来分析模型的预测性能，并支持向量机技术，这些技术在精度，召回和F测量等性能度量方面产生了相当好的结果。

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