Lana Yeganova
Lana Yeganova
Verified email at mail.nih.gov
Title
Cited by
Cited by
Year
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
1452015
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
812013
Meshable: Searching PubMed Abstracts by Utilizing MeSH and MeSH-Derived Topical Terms
S Kim, L Yeganova, WJ Wilbur
Bioinformatics, 2016
332016
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
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
162009
Retro: concept-based clustering of biomedical topical sets
L Yeganova, W Kim, S Kim, WJ Wilbur
Bioinformatics 30 (22), 3240-3248, 2014
152014
Isotonic regression under lipschitz constraint
L Yeganova, WJ Wilbur
Journal of optimization theory and applications 141 (2), 429-443, 2009
152009
The synergy between PAV and AdaBoost
WJ Wilbur, L Yeganova, W Kim
Machine Learning 61 (1), 71-103, 2005
152005
PubMed Phrases, an open set of coherent phrases for searching biomedical literature
S Kim, L Yeganova, DC Comeau, WJ Wilbur, Z Lu
Scientific data 5 (1), 1-11, 2018
142018
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
Hidden Markov models and optimized sequence alignments
L Smith, L Yeganova, WJ Wilbur
Computational biology and chemistry 27 (1), 77-84, 2003
142003
Machine learning with naturally labeled data for identifying abbreviation definitions
L Yeganova, DC Comeau, WJ Wilbur
BMC bioinformatics 12 (3), 1-8, 2011
132011
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
102010
Finding biomedical categories in MedlineŽ
L Yeganova, W Kim, DC Comeau, WJ Wilbur
Journal of biomedical semantics 3 (3), 1-9, 2012
92012
Findings of the wmt 2020 biomedical translation shared task: Basque, italian and russian as new additional languages
R Bawden, G Di Nunzio, C Grozea, I Unanue, A Yepes, N Mah, ...
5th Conference on Machine Translation, 2020
82020
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
82015
Identifying well-formed biomedical phrases in MEDLINEŽ text
W Kim, L Yeganova, DC Comeau, WJ Wilbur
Journal of biomedical informatics 45 (6), 1035-1041, 2012
62012
Topics in machine learning for biomedical literature analysis and text retrieval
RI Doğan, L Yeganova
Journal of biomedical semantics 3 (3), 1-2, 2012
62012
Navigating the landscape of COVID-19 research through literature analysis: a bird's eye view
L Yeganova, R Islamaj, Q Chen, R Leaman, A Allot, CH Wei, DC Comeau, ...
arXiv preprint arXiv:2008.03397, 2020
52020
The system can't perform the operation now. Try again later.
Articles 1–20