Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning.
<h4>Background</h4>Electronic health records are invaluable for medical research, but much of the information is recorded as unstructured free text which is time-consuming to review manually.<h4>Aim</h4>To develop an algorithm to identify relevant free texts automatically bas...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2012-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0030412&type=printable |
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