Essential Elements of Natural Language Processing: What the Radiologist Should Know.

Clicks: 409
ID: 51918
2019
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Abstract
Natural 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.
Reference Key
chen2019essentialacademic Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Chen, Po-Hao;
Journal Academic radiology
Year 2019
DOI
S1076-6332(19)30417-9
URL
Keywords
Deep learning artificial intelligence natural language processing text mining structured reporting

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