Article

An Unsupervised Error Detection Methodology for Detecting Mislabels in Healthcare Analytics

2024-07-04

Abstract excerpt

Medical datasets may be imbalanced and contain errors due to subjective test results and clinical variability. The poor quality of original data affects classification accuracy and reliability. Hence, detecting abnormal samples in the dataset can help clinicians make better decisions. In this study, we propose an unsupervised error detection method using patterns discovered by the Pattern Discovery and Disentangle...

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Literature Corpus work: 6ca5dd39-8494-58a4-b469-3264fdf58a72
DOI: 10.20944/preprints202407.0425.v1

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