What is it about?
Accurate diagnosis of diseases is important for medical practice. This article breaks new ground by proposing methods for biomarker performance evaluation that do not suffer from key issues that affect the performance of most applied approaches in practice, such as AUC (Area under the Curve) and the Youden Index. The proposed methods are particularly tailored for medical and genomic studies.
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Why is it important?
The most widely used metrics of biomarker performance evaluation---the AUC (Area under the Curve) and the Youden Index---suffer from key issues that question their reliability. This article proposes for the first time novel statistical methods for biomarker performance evaluation that do not suffer from those issues.
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This page is a summary of: Affinity-based measures of biomarker performance evaluation, Statistical Methods in Medical Research, May 2019, SAGE Publications, DOI: 10.1177/0962280219846157.
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