Literature DB >> 17317291

Evaluation of training with an annotation schema for manual annotation of clinical conditions from emergency department reports.

Wendy W Chapman1, John N Dowling, George Hripcsak.   

Abstract

OBJECTIVE: Determine whether agreement among annotators improves after being trained to use an annotation schema that specifies: what types of clinical conditions to annotate, the linguistic form of the annotations, and which modifiers to include.
METHODS: Three physicians and 3 lay people individually annotated all clinical conditions in 23 emergency department reports. For annotations made using a Baseline Schema and annotations made after training on a detailed annotation schema, we compared: (1) variability of annotation length and number and (2) annotator agreement, using the F-measure.
RESULTS: Physicians showed higher agreement and lower variability after training on the detailed annotation schema than when applying the Baseline Schema. Lay people agreed with physicians almost as well as other physicians did but showed a slower learning curve.
CONCLUSION: Training annotators on the annotation schema we developed increased agreement among annotators and should be useful in generating reference standard sets for natural language processing studies. The methodology we used to evaluate the schema could be applied to other types of annotation or classification tasks in biomedical informatics.

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Year:  2007        PMID: 17317291     DOI: 10.1016/j.ijmedinf.2007.01.002

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  13 in total

1.  Effectiveness of lexico-syntactic pattern matching for ontology enrichment with clinical documents.

Authors:  K Liu; W W Chapman; G Savova; C G Chute; N Sioutos; R S Crowley
Journal:  Methods Inf Med       Date:  2010-11-08       Impact factor: 2.176

2.  Building gold standard corpora for medical natural language processing tasks.

Authors:  Louise Deleger; Qi Li; Todd Lingren; Megan Kaiser; Katalin Molnar; Laura Stoutenborough; Michal Kouril; Keith Marsolo; Imre Solti
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

3.  Automatic identification of heart failure diagnostic criteria, using text analysis of clinical notes from electronic health records.

Authors:  Roy J Byrd; Steven R Steinhubl; Jimeng Sun; Shahram Ebadollahi; Walter F Stewart
Journal:  Int J Med Inform       Date:  2013-01-11       Impact factor: 4.046

4.  Developing a manually annotated clinical document corpus to identify phenotypic information for inflammatory bowel disease.

Authors:  Brett R South; Shuying Shen; Makoto Jones; Jennifer Garvin; Matthew H Samore; Wendy W Chapman; Adi V Gundlapalli
Journal:  Summit Transl Bioinform       Date:  2009-03-01

5.  Analysis of False Positive Errors of an Acute Respiratory Infection Text Classifier due to Contextual Features.

Authors:  Brett R South; Shuying Shen; Wendy W Chapman; Sylvain Delisle; Matthew H Samore; Adi V Gundlapalli
Journal:  Summit Transl Bioinform       Date:  2010-03-01

6.  Evaluating the impact of pre-annotation on annotation speed and potential bias: natural language processing gold standard development for clinical named entity recognition in clinical trial announcements.

Authors:  Todd Lingren; Louise Deleger; Katalin Molnar; Haijun Zhai; Jareen Meinzen-Derr; Megan Kaiser; Laura Stoutenborough; Qi Li; Imre Solti
Journal:  J Am Med Inform Assoc       Date:  2013-09-03       Impact factor: 4.497

7.  Expansion of medical vocabularies using distributional semantics on Japanese patient blogs.

Authors:  Magnus Ahltorp; Maria Skeppstedt; Shiho Kitajima; Aron Henriksson; Rafal Rzepka; Kenji Araki
Journal:  J Biomed Semantics       Date:  2016-09-26

8.  ADEPt, a semantically-enriched pipeline for extracting adverse drug events from free-text electronic health records.

Authors:  Ehtesham Iqbal; Robbie Mallah; Daniel Rhodes; Honghan Wu; Alvin Romero; Nynn Chang; Olubanke Dzahini; Chandra Pandey; Matthew Broadbent; Robert Stewart; Richard J B Dobson; Zina M Ibrahim
Journal:  PLoS One       Date:  2017-11-09       Impact factor: 3.240

9.  Developing a manually annotated clinical document corpus to identify phenotypic information for inflammatory bowel disease.

Authors:  Brett R South; Shuying Shen; Makoto Jones; Jennifer Garvin; Matthew H Samore; Wendy W Chapman; Adi V Gundlapalli
Journal:  BMC Bioinformatics       Date:  2009-09-17       Impact factor: 3.169

10.  Mining FDA drug labels for medical conditions.

Authors:  Qi Li; Louise Deleger; Todd Lingren; Haijun Zhai; Megan Kaiser; Laura Stoutenborough; Anil G Jegga; Kevin Bretonnel Cohen; Imre Solti
Journal:  BMC Med Inform Decis Mak       Date:  2013-04-24       Impact factor: 2.796

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