在医疗保健中使用机器学习算法预测糖尿病

M. A. Sarwar, Nasir Kamal, Wajeeha Hamid, M. A. Shah
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引用次数: 111

摘要

有几种机器学习技术可用于对不同领域的大数据进行预测分析。医疗保健中的预测分析是一项具有挑战性的任务,但最终可以帮助从业者根据大数据及时做出有关患者健康和治疗的决策。本文讨论了医疗保健中的预测分析,在本研究工作中使用了六种不同的机器学习算法。为了实验目的,获得了一个患者病历数据集,并在数据集上应用了六种不同的机器学习算法。讨论并比较了应用算法的性能和精度。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。本文旨在帮助医生和从业者使用机器学习技术进行糖尿病的早期预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of Diabetes Using Machine Learning Algorithms in Healthcare
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.
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