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Evaluating performance of health care facilities at meeting HIV-indicator reporting requirements in Kenya: an application of K-means clustering algorithm

机译：在肯尼亚达到艾滋病病毒指标报告要求时评估医疗设施的表现：K-Means聚类算法的应用

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摘要

Summary of some of the related works evaluating various dimensions of data quality

机译：一些相关工程的摘要评估了数据质量的各种维度

著录项

期刊名称 BMC Medical Informatics and Decision Making
作者
Milka Bochere Gesicho; Martin Chieng Were; Ankica Babic;
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作者单位

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年(卷),期 2021(-1),-1
年度 2021
页码 -1
总页数 18
原文格式 PDF
正文语种
中图分类情报学;
关键词
K-means clustering; Completeness; Timeliness; Performance; DHIS2;

机译：K-mears聚类;完整性;及时性;性能;DHIS2;

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专利

1. Evaluating performance of health care facilities at meeting HIV-indicator reporting requirements in Kenya: an application of K-means clustering algorithm [J] . Milka Bochere Gesicho, Martin Chieng Were, Ankica Babic BMC Medical Informatics and Decision Making . 2021,第1期

机译：评估肯尼亚艾滋病病毒指标报告要求的医疗设施的表现：K-Means聚类算法的应用
2. Evaluate the performance of K-Means and the fuzzy C-Means algorithms to formation balanced clusters in wireless sensor networks [J] . Ali Abdul-hussian Hassan, Wahidah Shah, Mohd Fairuz Iskandar Othman, International Journal of Electrical and Computer Engineering . 2020,第2期

机译：评估K-Means的性能和模糊C型算法在无线传感器网络中形成平衡集群
3. Perspectives and concerns of clients at primary health care facilities involved in evaluation of a national mental health training programme for primary care in Kenya [J] . Caleb Othieno, Rachel Jenkins, Stephen Okeyo, International Journal of Mental Health Systems . 2013,第7期

机译：初级卫生保健机构客户参与肯尼亚国家初级保健精神卫生培训计划评估的观点和关注
4. K-Means Clustering in Monitoring Facility Reporting of HIV Indicator Data: Case of Kenya [C] . Milka B. Gesicho, Ankica Babic, Martin C. Were International Conference on Informatics, Management, and Technology in Healthcare . 2020

机译：K-mears在监测艾滋病指标数据报告中的聚类：肯尼亚案例
5. Hardware Implementation and Performance Evaluation of K-Means and K-Means++ Clustering Algorithms [D] . Singh, Manisha . 2019

机译：K-Means和K-Means ++聚类算法的硬件实现和性能评估
6. Does Determination of Initial Cluster Centroids Improve the Performance of K-Means Clustering Algorithm? Comparison of Three Hybrid Methods by Genetic Algorithm Minimum Spanning Tree and Hierarchical Clustering in an Applied Study [O] . Saeedeh Pourahmad, Atefeh Basirat, Amir Rahimi, 2020

机译：初始簇质心的确定是否提高了K-Means聚类算法的性能？应用研究中遗传算法最小生成树和分层聚类的三种混合方法的比较
7. Does Determination of Initial Cluster Centroids Improve the Performance of K-Means Clustering Algorithm? Comparison of Three Hybrid Methods by Genetic Algorithm, Minimum Spanning Tree, and Hierarchical Clustering in an Applied Study [O] . Saeedeh Pourahmad, Atefeh Basirat, Amir Rahimi, 2020

机译：初始簇质心的确定是否提高了K-Means聚类算法的性能？应用研究中遗传算法，最小生成树和分层聚类的三种混合方法的比较
8. K-Means Re-Clustering Algorithmic Options with Quantifiable Performance Comparisons [R] . Meyer, A. W., Paglieroni, D. W., Astaneh, C. 2002

机译：K-means通过可量化的性能比较重新聚类算法选项

Evaluating performance of health care facilities at meeting HIV-indicator reporting requirements in Kenya: an application of K-means clustering algorithm

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