Automatic extraction of 12 cardiovascular concepts from German discharge letters using pre-trained language models: $hPhillip Richter-Pechanski, Nicolas A Geis, Christina Kiriakou, Dominic M Schwab and Christoph Dieterich
Objective A vast amount of medical data is still stored in unstructured text documents. We present an automated method of information extraction from German uns...
Gespeichert in:
| Hauptverfasser: | , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
November 26, 2021
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| In: |
Digital health
Year: 2021, Jahrgang: 7, Pages: 1-10 |
| ISSN: | 2055-2076 |
| DOI: | 10.1177/20552076211057662 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1177/20552076211057662 Verlag, lizenzpflichtig, Volltext: https://journals.sagepub.com/doi/10.1177/20552076211057662 |
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| 245 | 1 | 0 | |a Automatic extraction of 12 cardiovascular concepts from German discharge letters using pre-trained language models |b $hPhillip Richter-Pechanski, Nicolas A Geis, Christina Kiriakou, Dominic M Schwab and Christoph Dieterich |
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| 520 | |a Objective A vast amount of medical data is still stored in unstructured text documents. We present an automated method of information extraction from German uns... | ||
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