Lana Yeganova
Lana Yeganova
Geverifieerd e-mailadres voor mail.nih.gov
Titel
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Jaar
Extracting drug–drug interactions from literature using a rich feature-based linear kernel approach
S Kim, H Liu, L Yeganova, WJ Wilbur
Journal of biomedical informatics 55, 23-30, 2015
1112015
Author name disambiguation for PubMed
W Liu, R Islamaj Doğan, S Kim, DC Comeau, W Kim, L Yeganova, Z Lu, ...
Journal of the American Society for Information Science and Technology, 2013
612013
Identification of related gene/protein names based on an HMM of name variations
L Yeganova, L Smith, WJ Wilbur
Computational Biology and Chemistry 28 (2), 97-107, 2004
282004
Meshable: Searching PubMed Abstracts by Utilizing MeSH and MeSH-Derived Topical Terms
S Kim, L Yeganova, WJ Wilbur
Bioinformatics, 2016
252016
How to interpret PubMed queries and why it matters
L Yeganova, DC Comeau, W Kim, WJ Wilbur
Journal of the American Society for Information Science and Technology 60 (2 …, 2009
152009
Finding abbreviations in biomedical literature: three BioC-compatible modules and four BioC-formatted corpora
R Islamaj Doğan, DC Comeau, L Yeganova, WJ Wilbur
Database 2014, 2014
142014
Text mining techniques for leveraging positively labeled data
L Yeganova, DC Comeau, W Kim, WJ Wilbur
Proceedings of BioNLP 2011 Workshop, 155-163, 2011
142011
Retro: concept-based clustering of biomedical topical sets
L Yeganova, W Kim, S Kim, WJ Wilbur
Bioinformatics 30 (22), 3240-3248, 2014
132014
Isotonic regression under lipschitz constraint
L Yeganova, WJ Wilbur
Journal of optimization theory and applications 141 (2), 429-443, 2009
132009
Hidden Markov models and optimized sequence alignments
L Smith, L Yeganova, WJ Wilbur
Computational Biology and Chemistry 27 (1), 77-84, 2003
132003
Machine learning with naturally labeled data for identifying abbreviation definitions
L Yeganova, DC Comeau, WJ Wilbur
BMC bioinformatics 12 (3), 1-8, 2011
122011
The synergy between PAV and AdaBoost
WJ Wilbur, L Yeganova, W Kim
Machine Learning 61 (1-3), 71-103, 2005
122005
PubMed Phrases, an open set of coherent phrases for searching biomedical literature
S Kim, L Yeganova, DC Comeau, WJ Wilbur, Z Lu
Scientific data 6 (1), 1-9, 2019
112019
Finding biomedical categories in Medline®
L Yeganova, W Kim, DC Comeau, WJ Wilbur
Journal of biomedical semantics 3 (S3), S3, 2012
92012
Identifying abbreviation definitions machine learning with naturally labeled data
L Yeganova, DC Comeau, WJ Wilbur
2010 Ninth International Conference on Machine Learning and Applications …, 2010
92010
Summarizing Topical Contents from PubMed Documents Using a Thematic Analysis
S Kim, L Yeganova, WJ Wilbur
Conference on Empirical Methods on Natural Language Processing (EMNLP 2015 …, 2015
62015
Identifying well-formed biomedical phrases in MEDLINE® text
W Kim, L Yeganova, DC Comeau, WJ Wilbur
Journal of biomedical informatics 45 (6), 1035-1041, 2012
62012
MeSH-based dataset for measuring the relevance of text retrieval
WG Kim, L Yeganova, DC Comeau, WJ Wilbur, Z Lu
Proceedings of the BioNLP 2018 workshop, 161-165, 2018
42018
A Field Sensor: computing the composition and intent of PubMed queries
L Yeganova, W Kim, DC Comeau, WJ Wilbur, Z Lu
Database 2018, 2018
42018
Topics in machine learning for biomedical literature analysis and text retrieval
RI Doğan, L Yeganova
Journal of biomedical semantics 3 (3), 1-2, 2012
42012
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Artikelen 1–20