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NegFinder: A Web Service for Identifying Negation Signals and Their Scopes

Kazuki Fujikawa, Kazuhiro Seki, Kuniaki Uehara
2013 IPSJ Transactions on Bioinformatics  
This paper reports on our work on a hybrid approach to negation identification combining statistical and heuristic approaches and describes an implementation of the approach, named NegFinder, as a Web  ...  This is especially problematic in the biomedical domain since scientific findings and clinical records often contain negated expressions to state negative effects or the absence of symptoms.  ...  This is especially problematic in the biomedical and clinical domains since scientific findings or clinical records often include negated and/or uncertain expressions to state negative effects revealed  ... 
doi:10.2197/ipsjtbio.6.29 fatcat:wmfmtcf4tnb6phgeuteb2glezi

Detecting Negated and Uncertain Information in Biomedical and Review Texts

Noa P. Cruz Díaz
2013 Recent Advances in Natural Language Processing  
In the biomedical domain, the existence of a corpus annotated for negation, speculation and their scope has made it possible for the development of a machine learning system to automatically detect these  ...  On the other hand, in the review domain, the absence of an annotated corpus with this kind of information has led us to carry out the annotation for negation, speculation and their scope of a set of reviews  ...  To address this limitation in automatically detecting negations in clinical radiology reports, they proposed a novel hybrid approach, combining regular expression matching with grammatical parsing.  ... 
dblp:conf/ranlp/Diaz13 fatcat:zo2pzndc6zdlvhbnwaw4en2duu

Negation and Speculation in NLP: A Survey, Corpora, Methods, and Applications

Ahmed Mahany, Heba Khaled, Nouh Sabri Elmitwally, Naif Aljohani, Said Ghoniemy
2022 Applied Sciences  
in biomedical data.  ...  In some NLP applications, inclusion of a system that is negation- and speculation-aware improves performance, yet this aspect is still not addressed or considered an essential step.  ...  The authors proposed a hybrid machine learning approach with semantic, syntactic features to classify an event as certain or uncertain.  ... 
doi:10.3390/app12105209 fatcat:jzm5hjhcqbbr5ck6cosat7n5zq

Effects of Negation and Uncertainty Stratification on Text-Derived Patient Profile Similarity

Luke T. Slater, Andreas Karwath, Robert Hoehndorf, Georgios V. Gkoutos
2021 Frontiers in Digital Health  
In this work, we evaluate how inclusion and disclusion of negated and uncertain mentions of concepts from text-derived phenotypes affects similarity of patients, and the use of those profiles to predict  ...  Semantic similarity is a useful approach for comparing patient phenotypes, and holds the potential of an effective method for exploiting text-derived phenotypes for differential diagnosis, text and document  ...  ACKNOWLEDGMENTS We would like to thank Dr. Paul Schofield for helpful conversations and provision of computational resources.  ... 
doi:10.3389/fdgth.2021.781227 pmid:34939069 pmcid:PMC8685209 fatcat:2lm3lhxsxnfsnnhozy76sz5jzq

The BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes

Veronika Vincze, György Szarvas, Richárd Farkas, György Móra, János Csirik
2008 BMC Bioinformatics  
Detecting uncertain and negative assertions is essential in most BioMedical Text Mining tasks where, in general, the aim is to derive factual knowledge from textual data.  ...  This article reports on a corpus annotation project that has produced a freely available resource for research on handling negation and uncertainty in biomedical texts (we call this corpus the BioScope  ...  The authors wish to thank the anonymous reviewers for their useful suggestions and comments.  ... 
doi:10.1186/1471-2105-9-s11-s9 pmid:19025695 pmcid:PMC2586758 fatcat:fwaiyvo7bvcuvc4nu5xdqmtfji

Modality and Negation: An Introduction to the Special Issue

Roser Morante, Caroline Sporleder
2012 Computational Linguistics  
In this article, we will provide an overview of how modality and negation have been modeled in computational linguistics.  ...  Researchers have started to work on modeling factuality, belief and certainty, detecting speculative sentences and hedging, identifying contradictions, and determining the scope of expressions of modality  ...  They apply a hybrid, twostage approach to the scope resolution task.  ... 
doi:10.1162/coli_a_00095 fatcat:6p6vlzsrnfglve7fupa5ahykmu

Inferring the Scope of Negation in Biomedical Documents [chapter]

Miguel Ballesteros, Virginia Francisco, Alberto Díaz, Jesús Herrera, Pablo Gervás
2012 Lecture Notes in Computer Science  
In this paper we present a system that finds and annotates the scope of negation in English sentences. It infers which words are affected by negations by browsing dependency syntactic structures.  ...  The system presented in this paper can be accessed via web. 2 1 A negation cue is defined as the lexical marker that expresses negation [1]. 2  ...  Also, Huang and Lowe [8] implemented a hybrid approach to an automated negation detection system.  ... 
doi:10.1007/978-3-642-28604-9_30 fatcat:g4tx2eig3rey3la4fnprufduxq

Extracting structured information from free text pathology reports

Gunther Schadow, Clement J McDonald
2003 AMIA Annual Symposium Proceedings  
This paper describes the technical approach and reports on a preliminary evaluation study, designed to guide further development.  ...  We have developed a method that extracts structured information about specimens and their related findings in free-text surgical pathology reports.  ...  Special thanks to Drs. M. B ecich and J. Gilbertson (University of Pittsburgh) for the discussions that have sparked the inspiration to this approach.  ... 
pmid:14728240 pmcid:PMC1480213 fatcat:cc75g5tt7za6rfuqq77go3d4dy

Extracting Biomarker Information Applying Natural Language Processing and Machine Learning

Md. Tawhidul Islam, Mostafa Shaikh, Abhaya Nayak, Shoba Ranganathan
2010 Bioinformatics and Biomedical Engineering (iCBBE), International Conference on  
In this paper, we detail an approach to a very specific task of information extraction namely, extracting biomarker information in biomedical literature.  ...  Starting with the abstract of a given publication, we first identify the evaluative sentence(s) among other sentences by recognizing words and phrases in the text belonging to semantic categories of interest  ...  The task of the semantic category recognition SVM is to find and label the evaluative sentence in a document. The features used for this case are discussed in section II.  ... 
doi:10.1109/icbbe.2010.5514717 fatcat:jeuiavsuibfq3exbcbisimkebe

Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm

Brian E. Chapman, Sean Lee, Hyunseok Peter Kang, Wendy W. Chapman
2011 Journal of Biomedical Informatics  
In this paper we describe an application called peFinder for document-level classification of CT pulmonary angiography reports. peFinder is based on a generalized version of the ConText algorithm, a simple  ...  text processing algorithm for identifying features in clinical report documents. peFinder was used to answer questions about the disease state (pulmonary emboli present or absent), the certainty state  ...  Acknowledgment This work was supported in part by grants R01HL087119 and R01LM009427.  ... 
doi:10.1016/j.jbi.2011.03.011 pmid:21459155 pmcid:PMC3164892 fatcat:cslpa3jwznbyponq5utxrtw4qy

Integrating Speculation Detection and Deep Learning to Extract Lung Cancer Diagnosis from Clinical Notes

Oswaldo Solarte Pabón, Maria Torrente, Mariano Provencio, Alejandro Rodríguez-Gonzalez, Ernestina Menasalvas
2021 Applied Sciences  
To address this challenge, a hybrid approach that combines deep learning-based and rule-based methods is proposed.  ...  The approach integrates three steps: (i) lung cancer named entity recognition, (ii) negation and speculation detection, and (iii) relating the cancer diagnosis to a valid date.  ...  Sentence Analysis Previous rule-based approaches [53, 56, 58] use a stop word to find the negation or speculation scope.  ... 
doi:10.3390/app11020865 fatcat:odpnldls7jhetgh23zvss5lm6y

Supervised learning for the detection of negation and of its scope in French and Brazilian Portuguese biomedical corpora

Clément Dalloux, Vincent Claveau, Natalia Grabar, Lucas Emanuel Silva Oliveira, Claudia Maria Cabral Moro, Yohan Bonescki Gumiel, Deborah Ribeiro Carvalho
2020 Natural Language Engineering  
The methods show to be robust in both languages (Brazilian Portuguese and French) and in cross-domain (general and biomedical languages) contexts.  ...  Automatic detection of negated content is often a prerequisite in information extraction systems in various domains.  ...  In the biomedical field in particular, negation is very common and plays an important role.  ... 
doi:10.1017/s1351324920000352 fatcat:glbczme4dvhvdesd325fuaxklq

Comparing Transformer-based NER approaches for analysing textual medical diagnoses

Marco Polignano, Marco de Gemmis, Giovanni Semeraro
2021 Conference and Labs of the Evaluation Forum  
To this end, we focused on the name entity recognition task from medical documents and, in this work, we will discuss the results we obtained by our hybrid approach.  ...  The automated analysis of medical documents has grown in research interest in recent years as a consequence of the social relevance of the thematic and the difficulties often encountered with short and  ...  Acknowledgment This work has been supported by Apulia Region, Italy through the project "Un Assistente Dialogante Intelligente per il Monitoraggio Remoto di Pazienti" (Grant n. 10AC8FB6) in the context  ... 
dblp:conf/clef/PolignanoGS21 fatcat:dftxqeg37fc57mntppilu5pw6y

Deep Parsing at the CLEF2014 IE Task

Tigran Mkrtchyan, Daniel Sonntag
2014 Conference and Labs of the Evaluation Forum  
The system uses a lexicalized parser to annotate grammatical relations between diseases, disorders, and other constituents on a sentence level.  ...  High accuracy is most important for clinical decision support; the comparative results suggest that a deep parsing approach is suitable for this task, as we achieved acc = 0.822 and acc = 0.804 for the  ...  The main objective is to provide a hybrid information extraction (IE) platform based on handwritten rules in combination with semi-supervised machine learning approaches.  ... 
dblp:conf/clef/MkrtchyanS14 fatcat:yjsdkwkh3nb4zmre4gkplmqdri

Cross Disciplinary Consultancy to Bridge Public Health Technical Needs and Analytic Developers: Negation Detection Use Case

Mike Conway, Danielle Mowery, Amy Ising, Sumithra Velupillai, Son Doan, Julia Gunn, Michael Donovan, Caleb Wiedeman, Lance Ballester, Karl Soetebier, Catherine Tong, Burkom Howard
2018 Online Journal of Public Health Informatics  
of text processing algorithms to identify negated terms (i.e. negation detection) in free-text chief complaints and triage reports.  ...  The topic of this final consultancy, conducted at the University of Utah in January 2017, is focused on defining a roadmap for the development of algorithms, tools, and datasets for improving the capabilities  ...  Acknowledgements The organisation, preconference calls, and the consultancy itself were supported and funded by the Defense Threat Reduction Agency.  ... 
doi:10.5210/ojphi.v10i2.8944 pmid:30349627 pmcid:PMC6194092 fatcat:lk7y42bjtzdzlp3carnqwweqoy
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