Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010.
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Clinical research informatics: a conceptual perspectiveA Study of Neural Word Embeddings for Named Entity Recognition in Clinical TextNamed Entity Recognition in Chinese Clinical Text Using Deep Neural Network.Mining consumer health vocabulary from community-generated textLearning to identify treatment relations in clinical textChronology of your health events: approaches to extracting temporal relations from medical narrativesDiscovering body site and severity modifiers in clinical textsLearning to recognize phenotype candidates in the auto-immune literature using SVM re-rankingMining the pharmacogenomics literature--a survey of the state of the artFunctional evaluation of out-of-the-box text-mining tools for data-mining tasks.Entity recognition from clinical texts via recurrent neural network.A comprehensive study of named entity recognition in Chinese clinical text.Recognizing clinical entities in hospital discharge summaries using Structural Support Vector Machines with word representation features.Automated Assessment of Medical Students' Clinical Exposures according to AAMC Geriatric CompetenciesMapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological ResourceNamed entity recognition of follow-up and time information in 20,000 radiology reports.Ontology-guided feature engineering for clinical text classificationA comparative study of current Clinical Natural Language Processing systems on handling abbreviations in discharge summariesA Study of Concept Extraction Across Different Types of Clinical Notes.Knowledge-based biomedical word sense disambiguation: an evaluation and application to clinical document classification.A la Recherche du Temps Perdu: extracting temporal relations from medical text in the 2012 i2b2 NLP challenge.Combining rules and machine learning for extraction of temporal expressions and events from clinical narratives.An automatic system to identify heart disease risk factors in clinical texts over timeA hybrid model for automatic identification of risk factors for heart disease.Unsupervised biomedical named entity recognition: experiments with clinical and biological texts.Detecting concept mentions in biomedical text using hidden Markov model: multiple concept types at once or one at a time?A review of approaches to identifying patient phenotype cohorts using electronic health records.A Hybrid Approach to Extracting Disorder Mentions from Clinical Notes.Normalizing clinical terms using learned edit distance patterns.Assessing the role of a medication-indication resource in the treatment relation extraction from clinical text.Counting trees in Random Forests: Predicting symptom severity in psychiatric intake reports.Cue-based assertion classification for Swedish clinical text--developing a lexicon for pyConTextSwe.EliIE: An open-source information extraction system for clinical trial eligibility criteria.Bridging semantics and syntax with graph algorithms-state-of-the-art of extracting biomedical relations.DEEPEN: A negation detection system for clinical text incorporating dependency relation into NegEx.Classification of Contextual Use of Left Ventricular Ejection Fraction Assessments.A sequence labeling approach to link medications and their attributes in clinical notes and clinical trial announcements for information extraction.A study of active learning methods for named entity recognition in clinical textAutomatic identification of heart failure diagnostic criteria, using text analysis of clinical notes from electronic health records.In response to: Method of electronic health record documentation and quality of primary care
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P2860
Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010.
description
2011 nî lūn-bûn
@nan
2011 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Machine-learned solutions for ...... state of the art at i2b2 2010.
@ast
Machine-learned solutions for ...... state of the art at i2b2 2010.
@en
type
label
Machine-learned solutions for ...... state of the art at i2b2 2010.
@ast
Machine-learned solutions for ...... state of the art at i2b2 2010.
@en
prefLabel
Machine-learned solutions for ...... state of the art at i2b2 2010.
@ast
Machine-learned solutions for ...... state of the art at i2b2 2010.
@en
P2093
P2860
P1476
Machine-learned solutions for ...... state of the art at i2b2 2010.
@en
P2093
Berry de Bruijn
Colin Cherry
Joel Martin
Xiaodan Zhu
P2860
P304
P356
10.1136/AMIAJNL-2011-000150
P577
2011-05-12T00:00:00Z