A machine learning algorithm can identify patients with common variable immunodeficiency disease (CVID) from their electronic health records, according to a study published in the May 1 issue of Science Translational Medicine.
Due to the low prevalence and extensive heterogeneity in CVID phenotypes, resulting in delayed diagnoses and treatments, Ruth Johnson, Ph.D., from the University of California in Los Angeles, and colleagues presented a machine learning algorithm (PheNet) to identify patients with CVID from their electronic health records.
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