Enhancing Cluster Accuracy in Diabetes Multimorbidity With Dirichlet Process Mixture Models
Clustering of diabetic multimorbidity data from EHRs is challenging due to patient heterogeneity, high-dimensional variables, sensitivity to parameter settings, and high computational demands, which complicate clustering processes and may result in suboptimal clustering results. These complex and im...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10816607/ |
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