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Natural language processing: an introduction
Prakash M Nadkarni1, Lucila Ohno-Machado, Wendy W Chapman
1Yale University School of Medicine, New Haven, Connecticut, USA. prakash.nadkarni@yale.edu
Objectives:
To provide an overview and tutorial of natural language processing (NLP) and modern NLP-system design.
Target Audience:
This tutorial targets the medical informatics generalist who has limited acquaintance with the principles behind NLP and/or limited knowledge of the current state of the art.
Scope:
We describe the historical evolution of NLP, and summarize common NLP sub-problems in this extensive field. We then provide a synopsis of selected highlights of medical NLP efforts. After providing a brief description of common machine-learning approaches that are being used for diverse NLP sub-problems, we discuss how modern NLP architectures are designed, with a summary of the Apache Foundation's Unstructured Information Management Architecture. We finally consider possible future directions for NLP, and reflect on the possible impact of IBM Watson on the medical field.
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