Non-monotone transformation of biomarkers

Autor:	Duc-Khanh To, Monica Chiogna, Gianfranco Adimari
Přispěvatelé:	Adimari, Gianfranco, To, Duc-Khanh, Chiogna, Monica
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	Statistics and Probability Epidemiology Diagnostic accuracy 01 natural sciences 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Neyman–Pearson lemma Health Information Management classification accuracy Humans 030212 general & internal medicine 0101 mathematics ROC analysis Non monotone Parametric statistics Mathematics Discrete mathematics Lemma (mathematics) Diagnostic medicine Transformation (function) ComputingMethodologies_PATTERNRECOGNITION ROC Curve Binary classification Diagnostic medicine classification accuracy ROC analysis Neyman–Pearson lemma Biomarkers ROC analysi
Popis:	We comment here on a recent paper in this journal, on a non-monotone transformation of biomarkers aimed at improving diagnostic accuracy. We highlight that, in a binary classification problem, the proposed transformation finds its motivation in the Neyman–Pearson lemma, so that the underlying approach is very general and it is applicable to many parametric families, other than the normal one.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97362d1666b2fc325c3d1864a635457a http://hdl.handle.net/11585/817546 Zobrazit plný text záznamu