Topics in machine learning for biomedical literature analysis and text retrieval
Citation:
BMC Bioinformatics
2011
12(Suppl 3):I1
Volume 12 Supplement 3
Machine Learning for Biomedical Literature Analysis and Text Retrieval
Research
Edited by Lana Yeganova and Rezarta Islamaj Dogan
Machine Learning for Biomedical Literature Analysis and Text Retrieval in the International Conference for Machine Learning and Applications 2010. Go to conference site.
Washington, DC, USA12-14 December 2010
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A context-blocks model for identifying clinical relationships in patient records
Patient records contain valuable information regarding explanation of diagnosis, progression of disease, prescription and/or effectiveness of treatment, and more. Automatic recognition of clinically important ...
Citation: BMC Bioinformatics 2011 12(Suppl 3):S3 -
Collocation analysis for UMLS knowledge-based word sense disambiguation
The effectiveness of knowledge-based word sense disambiguation (WSD) approaches depends in part on the information available in the reference knowledge resource. Off the shelf, these resources are not optimize...
Citation: BMC Bioinformatics 2011 12(Suppl 3):S4 -
Improving a gold standard: treating human relevance judgments of MEDLINE document pairs
Given prior human judgments of the condition of an object it is possible to use these judgments to make a maximal likelihood estimate of what future human judgments of the condition of that object will be. How...
Citation: BMC Bioinformatics 2011 12(Suppl 3):S5 -
Machine learning with naturally labeled data for identifying abbreviation definitions
The rapid growth of biomedical literature requires accurate text analysis and text processing tools. Detecting abbreviations and identifying their definitions is an important component of such tools. Most exis...
Citation: BMC Bioinformatics 2011 12(Suppl 3):S6 -
A structural SVM approach for reference parsing
Automated extraction of bibliographic data, such as article titles, author names, abstracts, and references is essential to the affordable creation of large citation databases. References, typically appearing ...
Citation: BMC Bioinformatics 2011 12(Suppl 3):S7 -
Building a biomedical tokenizer using the token lattice design pattern and the adapted Viterbi algorithm
Tokenization is an important component of language processing yet there is no widely accepted tokenization method for English texts, including biomedical texts. Other than rule based techniques, tokenization i...
Citation: BMC Bioinformatics 2011 12(Suppl 3):S1 -
A system for de-identifying medical message board text
There are millions of public posts to medical message boards by users seeking support and information on a wide range of medical conditions. It has been shown that these posts can be used to gain a greater und...
Citation: BMC Bioinformatics 2011 12(Suppl 3):S2
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