Data Mining Framework for Discovering and Clustering Phenotypes of Atypical Diabetes
Authors' conclusion
DiscoverAD can be adapted to different datasets to identify and define phenotypes of participants with AD based on available clinical variables.
Study context
- Population
- Adults with diabetes in the Cameron County Hispanic Cohort (Study A) and multiethnic children with new-onset T1D in the Texas Children's Hospital Registry (Study B)
- Participants
- 278 vs 758
- Comparison
- Study A vs Study B
- Study An = 278
- Study Bn = 758
- Outcome
- AD frequency and phenotype clusters
Methodological detailsdata mining framework, cluster analysis
- Data mining framework
- Cluster analysis
Main finding
As reported in the abstract
Original publication
Data Mining Framework for Discovering and Clustering Phenotypes of Atypical Diabetes. J Clin Endocrinol Metab. Published 31 October 2022. doi:10.
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