Framework for Testing Robustness of Machine Learning-Based Classifiers

Framework for Testing Robustness of Machine Learning-Based Classifiers

There has been a rapid increase in the number of artificial intelligence (AI)/machine learning (ML)-based biomarker diagnostic classifiers in recent years. However, relatively little work has focused on assessing the robustness of these biomarkers, i.e., investigating the uncertainty of the AI/ML mo...

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Bibliographic Details
Main Authors: Joshua Chuah, Uwe Kruger, Ge Wang, Pingkun Yan, Juergen Hahn
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Journal of Personalized Medicine
Subjects:
classification
biomarker
machine learning
algorithms
artificial intelligence
omics analysis
Online Access:https://www.mdpi.com/2075-4426/12/8/1314

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