Table 3 Results of the best performance features (Unigrams, Bigrams, Concepts’ names and CUIs, and First level taxonomy) keeping the source of tokens (either title or abstract), using SVM-perf and a binary representation of features

SVM-perf unigram

0.395

0.654

0.492

SVM-perf bigram

0.414

0.675

0.513*

SVM-perf concepts

0.404

0.646

0.497*

SVM-perf CUIs

0.404

0.643

0.496*

SVM-perf first level taxonomy

0.351

0.653

0.456

SVM-perf TIAB unigram

0.398

0.659

0.496*

SVM-perf TIAB bigram

0.408

0.685

0.512*

SVM-perf TIAB Concepts

0.405

0.656

0.501*

SVM-perf TIAB CUIs

0.407

0.655

0.502*

SVM-perf TIAB first level taxonomy

0.376

0.610

0.465