Automated Preamble Detection in Dictated Medical Reports

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Abstract

Dictated medical reports very often feature a preamble containing metainformation about the report such as patient and physician names, location and name of the clinic, date of procedure, and so on. In the medical transcription process, the preamble is usually omitted from the final report, as it contains information already available in the electronic medical record. We present a method which is able to automatically identify preambles in medical dictations. The method makes use of state-of-the-art NLP techniques including word embeddings and Bi-LSTMs and achieves preamble detection performance superior to humans.

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APA

Salloum, W., Finley, G., Edwards, E., Miller, M., & Suendermann-Oeft, D. (2017). Automated Preamble Detection in Dictated Medical Reports. In BioNLP 2017 - SIGBioMed Workshop on Biomedical Natural Language Processing, Proceedings of the 16th BioNLP Workshop (pp. 287–295). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-2336

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