<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nadkarni, Prakash M</style></author><author><style face="normal" font="default" size="100%">Ohno-Machado, Lucila</style></author><author><style face="normal" font="default" size="100%">Chapman, Wendy W</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Natural language processing: an introduction.</style></title><secondary-title><style face="normal" font="default" size="100%">J Am Med Inform Assoc</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Am Med Inform Assoc</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Sep-Oct</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">544-51</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue></record></records></xml>