Berry de Bruijn
Berry de Bruijn
Vahvistettu sähköpostiosoite verkkotunnuksessa
PreBIND and Textomy–mining the biomedical literature for protein-protein interactions using a support vector machine
I Donaldson, J Martin, B De Bruijn, C Wolting, V Lay, B Tuekam, S Zhang, ...
BMC bioinformatics 4 (1), 1-13, 2003
Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010
B De Bruijn, C Cherry, S Kiritchenko, J Martin, X Zhu
Journal of the American Medical Informatics Association 18 (5), 557-562, 2011
Getting to the (c) ore of knowledge: mining biomedical literature
B De Bruijn, J Martin
International journal of medical informatics 67 (1-3), 7-18, 2002
ExaCT: automatic extraction of clinical trial characteristics from journal publications
S Kiritchenko, B De Bruijn, S Carini, J Martin, I Sim
BMC medical informatics and decision making 10 (1), 1-17, 2010
Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task
A Sarker, M Belousov, J Friedrichs, K Hakala, S Kiritchenko, F Mehryary, ...
Journal of the American Medical Informatics Association 25 (10), 1274-1283, 2018
Binary classifiers and latent sequence models for emotion detection in suicide notes
C Cherry, SM Mohammad, B De Bruijn
Biomedical informatics insights 5, BII. S8933, 2012
Automated information extraction of key trial design elements from clinical trial publications
B De Bruijn, S Carini, S Kiritchenko, J Martin, I Sim
AMIA Annual Symposium Proceedings 2008, 141, 2008
Literature mining in molecular biology
B De Bruijn, J Martin
National Research Council of Canada, 2002
A la Recherche du Temps Perdu: extracting temporal relations from medical text in the 2012 i2b2 NLP challenge
C Cherry, X Zhu, J Martin, B de Bruijn
Journal of the American Medical Informatics Association 20 (5), 843-848, 2013
Extracting keyphrases from spoken audio documents
A Désilets, B Bruijn, J Martin
Workshop on Information Retrieval Techniques for Speech Applications, 36-50, 2001
Detecting concept relations in clinical text: Insights from a state-of-the-art model
X Zhu, C Cherry, S Kiritchenko, J Martin, B De Bruijn
Journal of biomedical informatics 46 (2), 275-285, 2013
NRC at i2b2: one challenge, three practical tasks, nine statistical systems, hundreds of clinical records, millions of useful features
B de Bruijn, C Cherry, S Kiritchenko, J Martin, X Zhu
Proceedings of the 2010 i2b2/VA Workshop on Challenges in Natural Language …, 2010
Automatic SNOMED classification—a corpus-based method
LM De Bruijn, A Hasman, JW Arends
Computer methods and programs in biomedicine 54 (1-2), 115-122, 1997
Identifying wrist fracture patients with high accuracy by automatic categorization of X-ray reports
B de Bruijn, A Cranney, S O'Donnell, JD Martin, AJ Forster
Journal of the American Medical Informatics Association 13 (6), 696-698, 2006
NRC-Canada at SMM4H shared task: classifying Tweets mentioning adverse drug reactions and medication intake
S Kiritchenko, SM Mohammad, J Morin, B de Bruijn
arXiv preprint arXiv:1805.04558, 2018
Finding Gene Function using LitMiner
B Bruijn, J Martin
TREC, 451-459, 2003
Complementary approaches to searching MEDLINE may be sufficient for updating systematic reviews
M Sampson, B de Bruijn, C Urquhart, K Shojania
Journal of clinical epidemiology 78, 108-115, 2016
LitMiner: integration of library services within a bio-informatics application
J Demaine, J Martin, L Wei, B de Bruijn
Biomedical Digital Libraries 3 (1), 1-8, 2006
Extracting umls concepts from medical text using general and domain-specific deep learning models
KC Fraser, I Nejadgholi, B De Bruijn, M Li, A LaPlante, KZE Abidine
arXiv preprint arXiv:1910.01274, 2019
Evaluating Data Abstraction Assistant, a novel software application for data abstraction during systematic reviews: protocol for a randomized controlled trial
IJ Saldanha, CH Schmid, J Lau, K Dickersin, JA Berlin, J Jap, BT Smith, ...
Systematic reviews 5 (1), 1-11, 2016
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Artikkelit 1–20