Biomedical Content / Learning / New York / Anchorage / /
Company
Cambridge University Press / MIT Press / Integrated Medical Information Systems / Kendall / ACM Press / McGraw-Hill Companies / /
Country
United States / /
Currency
USD / / /
Event
Product Issues / Product Recall / /
Facility
National Library of Medicine / Biomedical Communications National Library of Medicine / /
IndustryTerm
search engines using clickthrough data / search engine optimization / decomposition algorithms / biomedical applications / fusion algorithm / retrieval algorithm / feature selection algorithm / natural cubic spline algorithm / retrieval algorithms / eļ¬cient image search / retrieval systems / be solved using decomposition algorithms / /
Organization
Cambridge University / National Institute of Health / Lister Hill National Center / Medicine and Biology Society / MIT / National Center for Health Statistics / Pattern Analysis and Machine Intelligence / /
Person
William W. Boonn / Brent J. Liu / George R. Thomaa / Sameer Antania / L. Rodney Longa / /
Position
representative / /
Product
graphs / Ranking SVM / graph / /
ProvinceOrState
Alaska / Massachusetts / /
PublishedMedium
IEEE Transactions on Pattern Analysis and Machine Intelligence / Clinical Medicine / /
Technology
PWS algorithm / using decomposition algorithms / x-ray / 2.2 The Ranking SVM algorithm The Ranking SVM algorithm / retrieval algorithms / retrieval algorithm / Data Mining / feature selection algorithm / search engine / fusion algorithm / machine learning / Smith-Waterman algorithm / natural cubic spline algorithm / Image informatics / two algorithms / ranking algorithm / Ranking SVM algorithm / Medical Imaging / using Smith-Waterman algorithm / /
Minimizing the semantic gap in biomedical content-based image retrieval[removed]]