Abstract
Natural language processing (NLP) emerged in the 1900s to support the wartime efforts. It’s dubious performance, however, slowed research initiatives until the 1960s when advances in machine learning provided novel approaches to text analysis. Increased processing speed and widespread availability of digital text accelerated this trend in the late 1990s. At the present time, there are extensive efforts to use NLP on clinical text and to incorporate this technology into software applications that support clinical care. In this chapter, the first of two about NLP, we will present: basic principles of NLP, the lexical resources required to produce high quality output from clinical text, the process (called annotation) of creating and NLP gold standard, the statistical methods used to evaluate and the role of shared tasks for evaluating and facilitating standardization in the field. Subsequent chapters will discuss ongoing research dedicated improving the quality and utility of NLP in the clinical setting.
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Acknowledgements
Dr. Savova’s work was supported in part by NIH grants U54LM008748 and 1U01HG006828. Drs. Deleger’s and Solti’s work was supported in part by NIH grant 5R00LM010227.
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Pestian, J.P., Deleger, L., Savova, G.K., Dexheimer, J.W., Solti, I. (2012). Natural Language Processing – The Basics. In: Hutton, J. (eds) Pediatric Biomedical Informatics. Translational Bioinformatics, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5149-1_9
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