Identifying Phenotypes of Atopic Dermatitis in a Longitudinal United States Cohort Using Unbiased Statistical Clustering.

Journal: The Journal of investigative dermatology

PMID: 31445921

No abstract available for this article.

Ronald Berna

Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Dermatology, University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address: ronald.berna@pennmedicine.upenn.edu.
Nandita Mitra

1 Department of Biostatistics & Epidemiology, University of Pennsylvania, Philadelphia, PA, USA.
Ole Hoffstad

Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Dermatology, University of Pennsylvania, Philadelphia, Pennsylvania.
Joy Wan

Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Dermatology, University of Pennsylvania, Philadelphia, Pennsylvania.
David J Margolis

Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Dermatology, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.

Age of Onset Child Child, Preschool Cluster Analysis Dermatitis, Atopic Diagnosis, Computer-Assisted Female Humans Infant Infant, Newborn Longitudinal Studies Machine Learning Male Phenotype Registries Severity of Illness Index United States

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