Weakly supervised learning of information structure of scientific abstracts-is it accurate enough to benefit real-world tasks in biomedicine?

Bioinformatics

Volumn 27, Issue 22, 2011, Pages 3179-3185

  Guo, Yufan ^a   Korhonen, Anna ^a   Silins, Ilona ^b   Stenius, Ulla ^b  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b KAROLINSKA INSTITUTE   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ARTIFICIAL INTELLIGENCE; CHEMICALLY INDUCED DISORDER; DATA MINING; DOCUMENTATION; EVALUATION; HUMAN; METHODOLOGY; NEOPLASM; RISK ASSESSMENT;

ABSTRACTING AND INDEXING AS TOPIC; ARTIFICIAL INTELLIGENCE; DATA MINING; HUMANS; NEOPLASMS; RISK ASSESSMENT;

EID: 80755144076     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btr536     Document Type: Article

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