Automated identification of diagnostic labelling errors in medicine.

Wolf E HautzMoritz M KündigRoger TschanzTanja BirrenbachAlexander SchusterThomas BürkleStefanie C HautzThomas C SauterGert Krummrey

Published in: Diagnosis (Berlin, Germany) (2021)

The trigger system to automatically identify diagnostic labeling error from routine health care data performs excellent, and is unaffected by the reference standards' limitations. It is however only applicable to cases with pairs of diagnoses, of which one must be more accurate or otherwise superior than the other, reflecting a prevalent definition of a diagnostic labeling error.

Keyphrases

healthcare
machine learning
emergency department
deep learning
high throughput
big data
patient safety
mass spectrometry