利用机器学习技术改善社区诊所的医疗服务

Shahidul Islam Khan, Arman Shaharia, Nazmul Islam, Md. Monirul Islam, A. S. M. Latiful Hoque
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引用次数: 1

摘要

孟加拉国的医疗保健在最近经历了快速增长。孟加拉国卫生部门每天产生大量数据。机器学习(ML)在医疗保健领域有着广泛的应用。本文重点介绍了机器学习在医疗保健中的应用。在本文中,我们使用ML技术来预测社区诊所的不同门诊数量。我们收集了14889名患者的数据集,时间跨度为508天,来自Sandwip的社区诊所。在我们的研究中,我们预测了一周中最大的女性和婴儿患者到社区诊所接受治疗的日期。因此,诊所当局可以安排相应的辅助人员。为此,我们使用了多元线性回归和支持向量回归。实验结果表明,该方法能够以最小的误差预测不同类型的门诊访问量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving Healthcare Services of Community Clinics using Machine Learning Techniques
Healthcare in Bangladesh has witnessed rapid growth in the recent past. A vast amount of data is generated in health sector of Bangladesh every day. Machine learning (ML) has a wide range of applications in healthcare. This paper highlights a brief overview of the applications of ML in healthcare. In this paper, we used ML techniques to predict different outpatient amounts of community clinics. We collected a dataset of 14889 patients within a time span of 508 days, from Community Clinics in Sandwip. In our research, we predicted the day of the week when maximum female and infant patients come into the community clinic for treatment. So the clinic authority may arrange support staffs accordingly. We used multiple linear regression and support vector regression for this purpose. Experimental results show that we could predict the amount of different types of outpatient visit with minimum error.
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