Article

Automated Detection of Poor-Quality Data: Case Studies in Healthcare

2021-04-28

Abstract excerpt

The detection and removal of poor-quality data in a training set is crucial to achieve high-performing AI models. In healthcare, data can be inherently poor-quality due to uncertainty or subjectivity, but as is often the case, the requirement for data privacy restricts AI practitioners from accessing raw training data, meaning manual visual verification of private patient data is not possible. Here we describe a n...

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Literature Corpus work: 703fef65-4a3f-564e-b05b-9a4c77c1df69
DOI: 10.21203/rs.3.rs-440365/v1

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