Do It Right! A Methodology for Successful NLP System Development
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Abstract (arXiv)
Natural language processing (NLP) is a common method for supplying data to clinical research and decision making by extracting information from electronic medical records. Numerous textbooks and tutorials describe specific algorithms and applications for text processing, yet algorithmic knowledge is only one ingredient of a successful NLP project. Drawing on the available literature, this paper presents a stepwise approach that applies the Systems Development Life Cycle (SDLC) to projects that rely on data extraction through language processing.
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References · 5
- 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,201
- 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 719
- 2016Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Changecited by 63
- 2023Improving Large Language Models for Clinical Named Entity Recognition via Prompt Engineeringcited by 7
- 2014Natural Language Processing in Biomedicine: A Unified System Architecture Overviewcited by 5
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