Addressing label noise for electronic health records: insights from computer vision for tabular data
The analysis of extensive electronic health records (EHR) datasets often calls for automated solutions, with machine learning (ML) techniques, including deep learning (DL), taking a lead role. One common task involves categorizing EHR data into predefined groups. However, the vulnerability of EHRs t...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
BioMed Central
2024
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