Advanced biomarker analysis for early Alzheimer's detection: a 3-class classification approach
By: Sierra Marquina Victor Miguel, Pardo Maria del Carmen, Franco-Pereira Alba Maria
Potential Business Impact:
Helps doctors tell apart three sicknesses better.
The receiver operating characteristic (ROC) curve is an important tool for the discrimination of two populations. However, in many settings, the diagnostic decision is not limited to a binary choice. ROC surfaces are considered as a natural generalization of ROC curves in three-class diagnostic problems and the Volume Under the ROC Surface (VUS) was proposed as an index for the assessment of the diagnostic accuracy of the marker under consideration. In this paper, we propose an overlap measure (OVL) in the case of three-class diagnostic problems. Specifically, parametric and non-parametric approaches for the estimation of OVL are introduced. We evaluate this measure through simulations and compare it with the well-known measure given by VUS. Furthermore, our proposal is applied to the clinical diagnosis of early stage Alzheimer's disease.
Similar Papers
The underlap coefficient as a measure of a biomarker's discriminatory ability
Methodology
Finds better ways to tell diseases apart.
ROC Analysis with Covariate Adjustment Using Neural Network Models: Evaluating the Role of Age in the Physical Activity-Mortality Association
Methodology
Helps doctors pick the best medicine for you.
Partial VOROS: A Cost-aware Performance Metric for Binary Classifiers with Precision and Capacity Constraints
Machine Learning (CS)
Helps doctors catch sick patients without too many false alarms.