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Extracting Diagnoses and Investigation Results from Unstructured Text in Electronic Health Records by Semi-Supervised Machine Learning
BACKGROUND: 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. AIM: To develop an algorithm to identify relevant free texts automatically based on labelled examples. METHODS: We...
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| Hauptverfasser: | , , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Public Library of Science
2012
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3261909/ https://ncbi.nlm.nih.gov/pubmed/22276193 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0030412 |
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