T. Lingren, Louise Deléger, Katalin Molnár, Haijun Zhai, J. Meinzen-Derr, M. Kaiser, Laura Stoutenborough, Qi Li, I. Solti
{"title":"为金标准语料库开发预注释临床笔记和临床试验公告:评估对注释速度和潜在偏倚的影响","authors":"T. Lingren, Louise Deléger, Katalin Molnár, Haijun Zhai, J. Meinzen-Derr, M. Kaiser, Laura Stoutenborough, Qi Li, I. Solti","doi":"10.1109/HISB.2012.33","DOIUrl":null,"url":null,"abstract":"In this study our aim was to present a series of experiments to evaluate the impact of pre-annotation: (1) on the speed of manual annotation of clinical notes and clinical trial announcements; and (2) test for potential bias if pre-annotation is utilized. The gold standard was 900 clinical trial announcements from clinicaltrials.gov website and 1655 clinical notes annotated for diagnoses, signs, symptoms, UMLS CUI and SNOMED CT codes. Two dictionary-based methods were used to pre-annotate the text. Annotation time savings ranged from 2.89% to 29.1% per entity. The pre-annotation did not reduce the IAA or annotator performance but reduced the time to annotate in every experiment. Dictionary-based pre-annotation is a feasible and practical method to reduce cost of annotation without introducing bias in the process.","PeriodicalId":375089,"journal":{"name":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Pre-annotating Clinical Notes and Clinical Trial Announcements for Gold Standard Corpus Development: Evaluating the Impact on Annotation Speed and Potential Bias\",\"authors\":\"T. Lingren, Louise Deléger, Katalin Molnár, Haijun Zhai, J. Meinzen-Derr, M. Kaiser, Laura Stoutenborough, Qi Li, I. Solti\",\"doi\":\"10.1109/HISB.2012.33\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study our aim was to present a series of experiments to evaluate the impact of pre-annotation: (1) on the speed of manual annotation of clinical notes and clinical trial announcements; and (2) test for potential bias if pre-annotation is utilized. The gold standard was 900 clinical trial announcements from clinicaltrials.gov website and 1655 clinical notes annotated for diagnoses, signs, symptoms, UMLS CUI and SNOMED CT codes. Two dictionary-based methods were used to pre-annotate the text. Annotation time savings ranged from 2.89% to 29.1% per entity. The pre-annotation did not reduce the IAA or annotator performance but reduced the time to annotate in every experiment. Dictionary-based pre-annotation is a feasible and practical method to reduce cost of annotation without introducing bias in the process.\",\"PeriodicalId\":375089,\"journal\":{\"name\":\"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HISB.2012.33\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HISB.2012.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pre-annotating Clinical Notes and Clinical Trial Announcements for Gold Standard Corpus Development: Evaluating the Impact on Annotation Speed and Potential Bias
In this study our aim was to present a series of experiments to evaluate the impact of pre-annotation: (1) on the speed of manual annotation of clinical notes and clinical trial announcements; and (2) test for potential bias if pre-annotation is utilized. The gold standard was 900 clinical trial announcements from clinicaltrials.gov website and 1655 clinical notes annotated for diagnoses, signs, symptoms, UMLS CUI and SNOMED CT codes. Two dictionary-based methods were used to pre-annotate the text. Annotation time savings ranged from 2.89% to 29.1% per entity. The pre-annotation did not reduce the IAA or annotator performance but reduced the time to annotate in every experiment. Dictionary-based pre-annotation is a feasible and practical method to reduce cost of annotation without introducing bias in the process.