Berry de Bruijn
National Research Council
30 Papers
142 Citations
Berry de Bruijn is an academic researcher from National Research Council. The author has contributed to research in topics: Computer science & Unified Medical Language System. The author has an hindex of 13, co-authored 30 publications. Previous affiliations of Berry de Bruijn include Ottawa Hospital Research Institute.
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Papers
PreBIND and Textomy - mining the biomedical literature for protein-protein interactions using a support vector machine
Ian Donaldson,Joel Martin,Berry de Bruijn,Cheryl Wolting,Vicki Lay,Brigitte Tuekam,Shudong Zhang,Berivan Baskin,Gary D. Bader,Gary D. Bader,Katerina Michalickova,Tony Pawson,Christopher W. V. Hogue +12 more
TL;DR: This work presents an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND.
ExaCT: automatic extraction of clinical trial characteristics from journal publications
TL;DR: An automatic information extraction system that assists users with locating and extracting key trial characteristics from full-text journal articles reporting on randomized controlled trials (RCTs) and can be extended to handle other characteristics and document types.
A randomized trial provided new evidence on the accuracy and efficiency of traditional vs. electronically annotated abstraction approaches in systematic reviews
Tianjing Li,Ian J. Saldanha,Jens Jap,Bryant T Smith,Joseph K. Canner,Susan Hutfless,Vernal Branch,Simona Carini,Wiley Chan,Berry de Bruijn,Byron C. Wallace,Sandra A. Walsh,Elizabeth J. Whamond,M. Hassan Murad,Ida Sim,Jesse A. Berlin,Joseph Lau,Kay Dickersin,Christopher H. Schmid +18 more
TL;DR: Independent abstraction may only be necessary for complex data items and DAA provides an audit trail that is crucial for reproducible research.
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Literature mining in molecular biology
Berry de Bruijn,Joel Martin +1 more
- 01 Jan 2002
TL;DR: This article divides automated reading into four general subtasks: text categorization, named entity tagging, fact extraction and collection-wide analysis, special attention is given to the domain particularities of molecular biology.
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À la Recherche du Temps Perdu: extracting temporal relations from medical text in the 2012 i2b2 NLP challenge
TL;DR: Methods for general relation extraction extended well to temporal relations, and gave top-ranked state-of-the-art results.
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