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bayesian hierarchical latent class model  (Johns Hopkins HealthCare)
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Johns Hopkins HealthCare bayesian hierarchical latent class model
Characteristics of prediction models developed to estimate the risk of disease reclassification during AS
Bayesian Hierarchical Latent Class Model, supplied by Johns Hopkins HealthCare, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Characteristics of prediction models developed to estimate the risk of disease reclassification during AS

Journal: Translational Andrology and Urology

Article Title: Active surveillance: a review of risk-based, dynamic monitoring

doi: 10.21037/tau.2017.12.27

Figure Lengend Snippet: Characteristics of prediction models developed to estimate the risk of disease reclassification during AS

Article Snippet: Johns Hopkins , Bayesian hierarchical latent class model , 964 patients from Johns Hopkins , GS ≥7 at radical prostatectomy.

Techniques: