Rui Zhu

TL;DR: In this paper, space maintainers in the primary and mixed dentition – a clinical guide is presented for the first time. (via Semantic Scholar)

author keywords: Bayesian bootstrap; Dirichlet process; MAR assumption; ROC surface; verification bias correction

MeSH headings : Bayes Theorem; Bias; Biomarkers, Tumor / blood; Biostatistics; CA-125 Antigen / blood; Carcinoma, Hepatocellular / blood; Carcinoma, Ovarian Epithelial / blood; Carcinoma, Ovarian Epithelial / diagnosis; Computer Simulation; Diagnostic Tests, Routine / statistics & numerical data; Female; Humans; Liver Neoplasms / blood; Male; Membrane Proteins / blood; Models, Statistical; Ovarian Neoplasms / blood; Ovarian Neoplasms / diagnosis; Prognosis; ROC Curve; Serum Albumin, Human; Statistics, Nonparametric; WAP Four-Disulfide Core Domain Protein 2 / metabolism

TL;DR: A Bayesian nonparametric approach is adopted by directly modeling the underlying distributions of the three categories by Dirichlet process mixture priors and it is found that the proposed method generally outperforms other approaches. (via Semantic Scholar)

author keywords: ROC surface; Verification bias correction; Trinormal model; MAR assumption

TL;DR: A Bayesian approach for estimating the ROC surface is proposed based on continuous data under a semi-parametric trinormality assumption and is applied to evaluate the performance of CA125 and HE4 in the diagnosis of epithelial ovarian cancer (EOC) as a demonstration. (via Semantic Scholar)