@inbook{aff7f0dad9514ad7863313643b401b4a,
title = "Bayesian Nonparametric Approaches for ROC Curve Inference",
abstract = "The development of medical diagnostic tests is of great importance in clinical practice, public health, and medical research. The receiver operating characteristic (ROC) curve is a popular tool for evaluating the accuracy of such tests. We review Bayesian nonparametric methods based on Dirichlet process mixtures and the Bayesian bootstrap for ROC curve estimation and regression. The methods are illustrated by means of data concerning diagnosis of lung cancer in women.",
keywords = "Biostatistics,Statistical Theory and Methods,Statistics for Life Sciences, Medicine, Health Sciences",
author = "{Calhau Fernandes Inacio De Carvalho}, Vanda and A. Jara and {de Carvalho}, M.",
year = "2015",
doi = "10.1007/978-3-319-19518-6_16",
language = "English",
isbn = "978-3-319-19517-9 978-3-319-19518-6",
series = "Frontiers in Probability and the Statistical Sciences",
publisher = "Springer-Verlag",
pages = "327--344",
editor = "R. Mitra and P. M{\"u}ller",
booktitle = "Nonparametric Bayesian Inference in Biostatistics",
}