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Natural Language Processing and Machine Learning Techniques Help Achieve a Better Medical Practice
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Author(s): Oana Frunza (University of Ottawa, Canada)and Diana Inkpen (University of Ottawa, Canada)
Copyright: 2012
Pages: 18
Source title:
Medical Applications of Intelligent Data Analysis: Research Advancements
Source Author(s)/Editor(s): Rafael Magdalena-Benedito (Intelligent Data Analysis Laboratory, University of Valencia, Spain), Emilio Soria-Olivas (Intelligent Data Analysis Laboratory, University of Valencia, Spain), Juan Guerrero Martínez (Intelligent Data Analysis Laboratory, University of Valencia, Spain), Juan Gómez-Sanchis (Intelligent Data Analysis Laboratory, University of Valencia, Spain)and Antonio Jose Serrano-López (Intelligent Data Analysis Laboratory, University of Valencia, Spain)
DOI: 10.4018/978-1-4666-1803-9.ch016
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Abstract
This book chapter presents several natural language processing (NLP) and machine learning (ML) techniques that can help achieve a better medical practice by means of extracting relevant medical information from the wealth of textual data. The chapter describes three major tasks: building intelligent tools that can help in the clinical decision making, tools that can automatically identify relevant medical information from the life-science literature, and tools that can extract semantic relations between medical concepts. Besides introducing and describing these tasks, methodological settings accompanied by representative results obtained on real-life data sets are presented.
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