ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2016
A Quantitative and Qualitative Evaluation of Sentence Boundary Detection for the Clinical Domain.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
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- Combining unsupervised, supervised and rule-based learning: the case of detecting patient allergies in electronic health records.BMC medical informatics and decision making · 2023Article
- Generalizability of machine learning methods in detecting adverse drug events from clinical narratives in electronic medical records.Frontiers in pharmacology · 2023Article
- Exploring optimal granularity for extractive summarization of unstructured health records: Analysis of the largest multi-institutional archive of health records in Japan.PLOS digital health · 2022Article
- Estimating Sentence-like Structure in Synthetic Languages Using Information Topology.Entropy (Basel, Switzerland) · 2022Article
- TAX-Corpus: Taxonomy based Annotations for Colonoscopy Evaluation.Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) · 2022Article
- The h-ANN Model: Comprehensive Colonoscopy Concept Compilation Using Combined Contextual Embeddings.Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) · 2022Article
- Automated Coding of Under-Studied Medical Concept Domains: Linking Physical Activity Reports to the International Classification of Functioning, Disability, and Health.Frontiers in digital health · 2021Article
- Reducing Physicians' Cognitive Load During Chart Review: A Problem-Oriented Summary of the Patient Electronic Record.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Hybrid Ensemble-Rule Algorithm for Improved MEDLINE® Sentence Boundary Detection.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Patient Triage by Topic Modeling of Referral Letters: Feasibility Study.JMIR medical informatics · 2020Article
- Cohort Selection for Clinical Trials From Longitudinal Patient Records: Text Mining Approach.JMIR medical informatics · 2019Article
- Recurrent Deep Network Models for Clinical NLP Tasks: Use Case with Sentence Boundary Disambiguation.Studies in health technology and informatics · 2019Article
- Deep Neural Architectures for Discourse Segmentation in E-Mail Based Behavioral Interventions.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- Adverse Drug Events Detection in Clinical Notes by Jointly Modeling Entities and Relations Using Neural Networks.Drug safety · 2019Article
- CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.Journal of the American Medical Informatics Association : JAMIA · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Sentence boundary detection (SBD) is a critical preprocessing task for many natural language processing (NLP) applications. However, there has been little work on evaluating how well existing methods for SBD perform in the clinical domain. We evaluate five popular off-the-shelf NLP toolkits on the task of SBD in various kinds of text using a diverse set of corpora, including the GENIA corpus of biomedical abstracts, a corpus of clinical notes used in the 2010 i2b2 shared task, and two general-domain corpora (the British National Corpus and Switchboard). We find that, with the exception of the cTAKES system, the toolkits we evaluate perform noticeably worse on clinical text than on general-domain text. We identify and discuss major classes of errors, and suggest directions for future work to improve SBD methods in the clinical domain. We also make the code used for SBD evaluation in this paper available for download at http://github.com/drgriffis/SBD-Evaluation.
Identifiers
27570656PMC5001746What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.