Bayesian framework for longitudinal EHR and genetic discovery [Nature, 27 Aug.]
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This entry was posted on November 8, 2026 at 12:26 am and is filed under Books, Statistics, University life with tags Bayesian generative model, cohort, disease, disease signature, electronic health record, finite mixtures, gaussian process, genetic variation, Genetics, Harvard University, heterogeneity, JASA, loadings, longitudinal studies, medical diagnoses, Nature, open access, sigmoïd. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.

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