Jingjing Yin Author

Research Article Open Access

Kullback-Leibler Divergence for Medical Diagnostics Accuracy and Cut-point Selection Criterion: How it is related to the Youden Index

Author(s):

Hani M. Samawi, Jingjing Yin, Xinyan Zhang, Lili Yu, Haresh Rochani, Robert Vogel  and Chen Mo

Recently, the Kullback-Leibler divergence (KL), which captures the disparity between two distributions, has been considered as an index for determining the diagnostic performance of markers. In this work, we propose using a total KL discrete version (TKLdiscrete), after the discretization of a continuous biomarker, as an optimization criterion for cut-point selection. We linked the proposed TKLdiscrete measure with the Youden index, which is the most commonly used cut-point selection criterion. In addition, we present theoretically and numerically the derived relations in situations of one cut-point (two categories) as well as multiple category markers under binary disease status. This study also investigates a variety of applications of KL divergence in medical diagnostics. For example... view more»

DOI: 10.37532/2329-9533.2020.9(2).168

Abstract HTML PDF