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We describe an approach to select semantically coherent specialty subsets based on the historical use of terminology by different service areas. Our approach uses rule-based and machine learning techniques to… Click to show full abstract
We describe an approach to select semantically coherent specialty subsets based on the historical use of terminology by different service areas. Our approach uses rule-based and machine learning techniques to obtain a reduced set of 29 specialties.
Keywords:
selection semantic;
healthcare services;
relevant healthcare;
services subsets;
semantic relevant
Journal Title: Studies in health technology and informatics
Year Published: 2018
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Journal Title: Studies in health technology and informatics
Year Published: 2018
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!