%0 Conference Paper %1 Yu:2005b %A Yu, Hong %A Sable, Carl %A Zhu, Hai Ran %B Proc. AAAI'05 Workshop on Question Answering in Restricted Domains %D 2005 %K question_classification question_answering biomedical %T Classifying Medical Questions based on an Evidence Taxonomy %U http://www.uwm.edu/~hongyu/publications.html %X We present supervised machine-learning approaches to automatically classify medical questions based on a hierarchical evidence taxonomy created by physicians. We show that SVMs is the best classifier for this task and that a ladder approach, which incorporates the knowledge representation of the hierarchical evidence taxonomy, leads to the highest performance. We have explored the use of features from a large, robust biomedical knowledge resource, namely, the Unified Medical Language System (UMLS), and we have found that performance is generally enhanced by including these features in addition to bag-of-words.

@inproceedings{Yu:2005b, abstract = {We present supervised machine-learning approaches to automatically classify medical questions based on a hierarchical evidence taxonomy created by physicians. We show that SVMs is the best classifier for this task and that a ladder approach, which incorporates the knowledge representation of the hierarchical evidence taxonomy, leads to the highest performance. We have explored the use of features from a large, robust biomedical knowledge resource, namely, the Unified Medical Language System (UMLS), and we have found that performance is generally enhanced by including these features in addition to bag-of-words.}, added-at = {2009-08-14T09:16:01.000+0200}, author = {Yu, Hong and Sable, Carl and Zhu, Hai Ran}, biburl = {https://www.bibsonomy.org/bibtex/2536edeb935472f74ddf66a0d4deb20fd/diego_ma}, booktitle = {Proc. AAAI'05 Workshop on Question Answering in Restricted Domains}, interhash = {53370a14e66634dd4250c7f2b8114ff3}, intrahash = {536edeb935472f74ddf66a0d4deb20fd}, keywords = {question_classification question_answering biomedical}, library = {Web (August 2009)}, timestamp = {2009-08-14T09:16:01.000+0200}, title = {Classifying Medical Questions based on an Evidence Taxonomy}, url = {http://www.uwm.edu/~hongyu/publications.html}, year = 2005 }