| Literature DB >> 31250693 |
Abstract
Cut-points selection is a key topic in the field of diagnostic studies. For binary classification, there exist several well-developed methods, some of which have been extended to three-class settings and beyond. This paper focuses on optimal cut-points selection methods for diseases with multiple ordinal stages. The purpose of this paper is two-fold: 1) to propose three new cut-points selection methods; and 2) to present a comprehensive simulation study to assess and compare the performance of all the available methods. Two real data sets, one from ovarian cancer and the other from pancreatic cancer, are analyzed.Entities:
Keywords: ROC curve; ROC surface; Youden index; area under ROC curve; volume under ROC surfac
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Year: 2019 PMID: 31250693 DOI: 10.1080/10543406.2019.1632876
Source DB: PubMed Journal: J Biopharm Stat ISSN: 1054-3406 Impact factor: 1.051