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  • 标题:Unsupervised Machine Learning for Co/Multimorbidity Analysis
  • 本地全文:下载
  • 作者:Shatrunjai Singh ; Swagata Karkare ; Sudhir Baswan
  • 期刊名称:International Journal of Statistics and Probability
  • 印刷版ISSN:1927-7032
  • 电子版ISSN:1927-7040
  • 出版年度:2018
  • 卷号:7
  • 期号:6
  • 页码:23
  • DOI:10.5539/ijsp.v7n6p23
  • 出版社:Canadian Center of Science and Education
  • 摘要:

    Although co/multimorbidities are associated with a significant increase in mortality, lack of quantitative exploratory techniques often impedes an in-depth analysis of their association. In the current study, we explore the clustering of co/multimorbid patients in the Texas patient population. We employ unsupervised agglomerative hierarchical clustering to find clusters of co/multimorbid patients within this population. Our analysis revealed the presence of nine distinct, clinically relevant clusters of co/multimorbidities within the study population of interest. This technique provides a quantitative exploratory analysis of the co/multimorbidities present in a specific population.

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