Text categorization models for identifying unproven cancer treatments on the web

Studies in Health Technology and Informatics

Volumn 129, Issue , 2007, Pages 968-972

  Aphinyanaphongs, Yin ^a   Aliferis, Constantin ^a,b,c  

^a VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^b VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c VANDERBILT INGRAM CANCER CENTER   (United States)

Author keywords

information storage and retrieval; internet; medical informatics; neoplasms; text categorization

Indexed keywords

INTERNET; LEARNING SYSTEMS; SEARCH ENGINES; TEXT PROCESSING;

ADVERSE OUTCOMES; ENGINE TECHNOLOGY; FEASIBILITY STUDIES; INFORMATION STORAGE AND RETRIEVAL; MACHINE LEARNING TECHNIQUES; MEDICAL INFORMATICS; NEOPLASMS; TEXT CATEGORIZATION;

WEBSITES;

ARTICLE; ARTIFICIAL INTELLIGENCE; FEASIBILITY STUDY; HUMAN; INFORMATION RETRIEVAL; INFORMATION SERVICE; INTERNET; NEOPLASM; QUACKERY; ROC CURVE; STANDARD;

ARTIFICIAL INTELLIGENCE; FEASIBILITY STUDIES; HUMANS; INFORMATION SERVICES; INFORMATION STORAGE AND RETRIEVAL; INTERNET; NEOPLASMS; QUACKERY; ROC CURVE;

EID: 35748929116     PISSN: 09269630     EISSN: 18798365     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

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