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Prediction of Diabetes Using Machine Learning Algorithms in Healthcare

机译:医疗机器学习算法预测糖尿病

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There are several machine learning techniques that are used to perform predictive analytics over big data in various fields. Predictive analytics in healthcare is a challenging task but ultimately can help practitioners make big data-informed timely decisions about patient's health and treatment. This paper discusses the predictive analytics in healthcare, six different machine learning algorithms are used in this research work. For experiment purpose, a dataset of patient's medical record is obtained and six different machine learning algorithms are applied on the dataset. Performance and accuracy of the applied algorithms is discussed and compared. Comparison of the different machine learning techniques used in this study reveals which algorithm is best suited for prediction of diabetes. This paper aims to help doctors and practitioners in early prediction of diabetes using machine learning techniques.
机译:有几种机器学习技术用于在各个领域的大数据上执行预测分析。医疗保健的预测分析是一个具有挑战性的任务,但最终可以帮助从业者对患者的健康和治疗提供大数据的及时决定。本文讨论了医疗保健的预测分析,在本研究工作中使用了六种不同的机器学习算法。对于实验目的,获得了患者的病历数据集,并在数据集上应用了六种不同的机器学习算法。讨论和比较了应用算法的性能和准确性。本研究中使用的不同机器学习技术的比较揭示了哪种算法最适合预测糖尿病。本文旨在利用机器学习技术帮助医生和从业者在早期预测糖尿病。

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