A metalearning approach to processing the scope of negation
Published 1 January 2009Open access
Roser Morante, Walter Daelemans
Citations153
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
A machine learning system that finds the scope of negation in biomedical texts by combines several classifiers and works in two phases and achieves the best results to date for this task.
Abstract
Finding negation signals and their scope in text is an important subtask in information extraction. In this paper we present a machine learning system that finds the scope of negation in biomedical texts. The system combines several classifiers and works in two phases. To investigate the robustness of the approach, the system is tested on the three subcorpora of the BioScope corpus representing different text types. It achieves the best results to date for this task, with an error reduction of 32.07% compared to current state of the art results.
Keywords
Computer ScienceBiochemistry, Genetics and Molecular Biology
IEEE Transactions on Information TheoryNearest neighbor pattern classification
16,134 Citations1967Thomas M. Cover, Peter E. Hart
The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
ScholarlyCommons (University of Pennsylvania)Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
12,978 Citations2001John Lafferty, Andrew McCallum +1 more
This work presents iterative parameter estimation algorithms for conditional random fields and compares the performance of the resulting models to HMMs and MEMMs on synthetic and natural-language data.
International Conference on Neural Information ProcessingAdvances in kernel methods: support vector learning
5,815 Citations1999Bernhard Schölkopf, Christopher J. C. Burges +1 more
Support vector machines for dynamic reconstruction of a chaotic system, Klaus-Robert Muller et al pairwise classification and support vector machines, Ulrich Kressel.
Journal of Biomedical InformaticsA Simple Algorithm for Identifying Negated Findings and Diseases in Discharge Summaries
1,121 Citations2001Wendy W. Chapman, Will Bridewell +3 more
It is concluded that with little implementation effort a simple regular expression algorithm for determining whether a finding or disease mentioned within narrative medical reports is present or absent can identify a large portion of the pertinent negatives from discharge summaries.
CoNLL-X shared task on multilingual dependency parsing
976 Citations2006Sabine Buchholz, Erwin Marsi
How treebanks for 13 languages were converted into the same dependency format and how parsing performance was measured is described and general conclusions about multi-lingual parsing are drawn.
Lecture notes in computer scienceDeveloping a Robust Part-of-Speech Tagger for Biomedical Text
439 Citations2005Yoshimasa Tsuruoka, Yuka Tateishi +5 more
Experimental results on the Wall Street Journal corpus, the GENIA corpus, and the PennBioIE corpus revealed that adding training data from a different domain does not hurt the performance of a tagger, and the authors' tagger exhibits very good precision on all these corpora.
BMC BioinformaticsThe BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes
420 Citations2008Veronika Vincze, György Szarvas +3 more
A corpus annotation project that has produced a freely available resource for research on handling negation and uncertainty in biomedical texts, which is also a good resource for the linguistic analysis of scientific and clinical texts.
Bidirectional inference with the easiest-first strategy for tagging sequence data
257 Citations2005Yoshimasa Tsuruoka, Jun’ichi Tsujii
This paper presents a bidirectional inference algorithm for sequence labeling problems such as part-of-speech tagging, named entity recognition and text chunking that can enumerate all possible decomposition structures and find the highest probability sequence together with the corresponding decomposition structure in polynomial time.
Journal of the American Medical Informatics AssociationUse of General-purpose Negation Detection to Augment Concept Indexing of Medical Documents: A Quantitative Study Using the UMLS
252 Citations2001Pradeep Mutalik, Aniruddha M. Deshpande +1 more
Test the hypothesis that most instances of negated concepts in dictated medical documents can be detected by a strategy that relies on tools developed for the parsing of formal (computer) languages-specifically, a lexical scanner that uses regular expressions to generate a finite state machine, and a parser that depends on a restricted subset of context-free grammars.
Journal of the American Medical Informatics AssociationA Novel Hybrid Approach to Automated Negation Detection in Clinical Radiology Reports
189 Citations2007Yang Huang, Henry Lowe
A novel hybrid approach, combining regular expression matching with grammatical parsing, can accurately locate negated concepts in clinical radiology reports not only when in close proximity to, but also at a distance from, negation signals.
The BioScope corpus
170 Citations2008György Szarvas, Veronika Vincze +2 more
A corpus annotation project that has produced a freely available resource for research on handling negation and uncertainty in biomedical texts and is called the BioScope corpus, which consists of medical free texts, biological full papers and biological scientific abstracts.
BMC Medical Informatics and Decision MakingA controlled trial of automated classification of negation from clinical notes
143 Citations2005Peter L. Elkin, Steven H. Brown +5 more
Information RetrievalNegation recognition in medical narrative reports
82 Citations2008Lior Rokach, Roni Romano +1 more
A new pattern learning method is presented for automatic identification of negative context in clinical narratives reports and its advantages are accuracy improvement compared to other machine learning methods, and much faster than manual knowledge engineering techniques with matching accuracy.
The GENIA project
80 Citations1999Nigel Collier, Jun'ichi Tsujii +8 more
The genome information acquisition project for automatically extracting biochemical information from journal papers and abstracts is presented, designed to aid in information extraction, retrieval and visualisation and to help reduce information overload on researchers.
Studies in health technology and informaticsContext-Sensitive Medical Information Retrieval
63 Citations2004Averbuch Mordechai, Tom H. Karson +3 more
The algorithm presented significantly improves the performance of information retrieval done on medical narratives and reduces the error rate from about 60%, when using context-insensitive retrieval, to nearly 100%.
BioinformaticsNegation of protein–protein interactions: analysis and extraction
55 Citations2007Olivia Sanchez-Graillet, Massimo Poesio
This work presents an analysis of the types of negative information that is reported, and a heuristic-based system using a full dependency parser to extract such information, and gets an initial corpus of negative protein-protein interactions as basis for the construction of larger ones.
Applying spelling error correction techniques for improving semantic role labelling
22 Citations2005Erik Tjong Kim Sang, Sander Canisius +2 more
This paper describes the approach to the CoNLL-2005 shared task: semantic role labelling, and applies different machine learning algorithms and combine their predictions to optimize generalization performance on the particular task.
A combined memory-based semantic role labeler of English
15 Citations2008Roser Morante, Walter Daelemans +1 more
A PWM solenoid operated valve control arrangement which substantially eliminates supply voltage dependent variability of the valve without the expense or inefficiency of a conventional voltage regulator.