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- Po-Hao Chen.
- Imaging Institute, Cleveland Clinic Foundation, 9500 Euclid Ave. - P34, Cleveland, OH 44195. Electronic address: chenp2@ccf.org.
- Acad Radiol. 2020 Jan 1; 27 (1): 6-12.
AbstractNatural language is ubiquitous in the workflow of medical imaging. Radiologists create and consume free text in their daily work, some of which can be amenable to enhancements through automatic processing. Recent advancements in deep learning and "artificial intelligence" have had a significant positive impact on natural language processing (NLP). This article discusses the history of how researchers have extracted data and encoded natural language information for analytical processing, starting from NLP's humble origins in hand-curated, linguistic rules. The evolution of medical NLP including vectorization, word embedding, classification, as well as its use in automated speech recognition, are also explored. Finally, the article will discuss the role of machine learning and neural networks in the context of significant, if incremental, improvements in NLP.Copyright © 2019 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
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