FasTag: Automatic text classification of unstructured medical narratives

Unstructured clinical narratives are continuously being recorded as part of delivery of care in electronic health records, and dedicated tagging staff spend considerable effort manually assigning clinical codes for billing purposes. Despite these efforts, however, label availability and accuracy are...

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Veröffentlicht in:	PloS one 2020-06, Vol.15 (6), p.e0234647-e0234647
Hauptverfasser:	Venkataraman, Guhan Ram, Pineda, Arturo Lopez, Bear Don't Walk Iv, Oliver J, Zehnder, Ashley M, Ayyar, Sandeep, Page, Rodney L, Bustamante, Carlos D, Rivas, Manuel A
Format:	Artikel
Sprache:	eng
Schlagworte:	Animals Annotations Artificial neural networks Automation Biology and Life Sciences Cancer Classification Clinical coding Clinical medicine Codes Computer and Information Sciences Data Mining Data processing Data storage Databases as Topic Decision trees Dictionaries Disease Domains Electronic health records Electronic medical records Electronic records Engineering and Technology Humans Long short-term memory Machine learning Management Medical coding Medical diagnosis Medical records Medicine and Health Sciences Methods Model accuracy Narrative Medicine Narratives Natural language processing Neural networks Oncology Physical work Recurrent neural networks Reproducibility of Results Research and Analysis Methods Schools Semantics Short term memory Software Species Specificity Tagging Technology application Unstructured data Veterinary colleges Veterinary medicine
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