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Change Point Estimation Based on a Weighted Consensus Clustering Approach with Multiple Steps (A Real Case in Health Care: Diabetic Patients).

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Title: Change Point Estimation Based on a Weighted Consensus Clustering Approach with Multiple Steps (A Real Case in Health Care: Diabetic Patients).
Authors: Gharegozloo, Mona1 (AUTHOR) gharegozloo.mona@gmail.com, Kamranrad, Reza1 (AUTHOR) r.kamranrad@semnan.ac.ir
Source: International Journal of Reliability, Quality & Safety Engineering. Jun2025, Vol. 32 Issue 3, p1-20. 20p.
Subjects: Fix-point estimation, Maximum likelihood statistics, Quality control charts, Cluster analysis (Statistics), People with diabetes
Abstract: One of the primary objectives of control charts is to accurately detect the occurrence of changes in statistical processes. This enables process analysts to identify the factors responsible for the change and take corrective actions. The clustering method is a practical approach that has been developed to estimate the time of change. In recent years, a new approach called weighted consensus clustering (WCC) has been introduced in the field of clustering analysis. This approach can be utilized to cluster different trends in process parameters, resulting in a final clustering that exhibits higher quality and stability compared to the initial clustering. One of the emerging aspects in the health care field is the use of new statistical approaches to rapid disease diagnosis. In this paper, a novel change point estimation scheme called WCC has been developed to detect changes in the diabetic patients' processes. In addition, to demonstrate the advantages of the proposed scheme, its performance is compared with an existing method known as maximum likelihood of clusters (CMLE) through simulation studies as well as a real case study in the healthcare system. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Reliability, Quality & Safety Engineering is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Change Point Estimation Based on a Weighted Consensus Clustering Approach with Multiple Steps (A Real Case in Health Care: Diabetic Patients).
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  Data: <searchLink fieldCode="AR" term="%22Gharegozloo%2C+Mona%22">Gharegozloo, Mona</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> gharegozloo.mona@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Kamranrad%2C+Reza%22">Kamranrad, Reza</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> r.kamranrad@semnan.ac.ir</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Reliability%2C+Quality+%26+Safety+Engineering%22">International Journal of Reliability, Quality & Safety Engineering</searchLink>. Jun2025, Vol. 32 Issue 3, p1-20. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Fix-point+estimation%22">Fix-point estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Maximum+likelihood+statistics%22">Maximum likelihood statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+control+charts%22">Quality control charts</searchLink><br /><searchLink fieldCode="DE" term="%22Cluster+analysis+%28Statistics%29%22">Cluster analysis (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22People+with+diabetes%22">People with diabetes</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: One of the primary objectives of control charts is to accurately detect the occurrence of changes in statistical processes. This enables process analysts to identify the factors responsible for the change and take corrective actions. The clustering method is a practical approach that has been developed to estimate the time of change. In recent years, a new approach called weighted consensus clustering (WCC) has been introduced in the field of clustering analysis. This approach can be utilized to cluster different trends in process parameters, resulting in a final clustering that exhibits higher quality and stability compared to the initial clustering. One of the emerging aspects in the health care field is the use of new statistical approaches to rapid disease diagnosis. In this paper, a novel change point estimation scheme called WCC has been developed to detect changes in the diabetic patients' processes. In addition, to demonstrate the advantages of the proposed scheme, its performance is compared with an existing method known as maximum likelihood of clusters (CMLE) through simulation studies as well as a real case study in the healthcare system. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Reliability, Quality & Safety Engineering is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1142/S0218539324500566
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 20
        StartPage: 1
    Subjects:
      – SubjectFull: Fix-point estimation
        Type: general
      – SubjectFull: Maximum likelihood statistics
        Type: general
      – SubjectFull: Quality control charts
        Type: general
      – SubjectFull: Cluster analysis (Statistics)
        Type: general
      – SubjectFull: People with diabetes
        Type: general
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      – TitleFull: Change Point Estimation Based on a Weighted Consensus Clustering Approach with Multiple Steps (A Real Case in Health Care: Diabetic Patients).
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            NameFull: Gharegozloo, Mona
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            NameFull: Kamranrad, Reza
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            – D: 01
              M: 06
              Text: Jun2025
              Type: published
              Y: 2025
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            – TitleFull: International Journal of Reliability, Quality & Safety Engineering
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