Numerical Eligibility Criteria in Clinical Protocols: Annotation, Automatic Detection and Interpretation

被引:0
|
作者
Claveau, Vincent [1 ]
Silva Oliveira, Lucas Emanuel [2 ]
Bouzille, Guillaume [3 ,4 ,5 ]
Cuggia, Marc [3 ,4 ,5 ]
Cabral Moro, Claudia Maria [2 ]
Grabar, Natalia [6 ]
机构
[1] CNRS, IRISA, Rennes, France
[2] PUCPR Pontificia Univ Catolica Parana, Curitiba, Parana, Brazil
[3] INSERM, LTSI, HBD, Rennes, France
[4] CHU Rennes, Rennes, France
[5] Univ Rennes 2, Rennes, France
[6] Univ Lille, CNRS, UMR 8163, STL, F-59000 Lille, France
关键词
Natural language processing; Supervised learning; Clinical trials; Patient eligibility; Numerical criteria;
D O I
10.1007/978-3-319-59758-4_22
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Clinical trials are fundamental for evaluating therapies and diagnosis techniques. Yet, recruitment of patients remains a real challenge. Eligibility criteria are related to terms but also to patient laboratory results usually expressed with numerical values. Both types of information are important for patient selection. We propose to address the processing of numerical values. A set of sentences extracted from clinical trials are manually annotated by four annotators. Four categories are distinguished: C (concept), V (numerical value), U (unit), O (out position). According to the pairs of annotators, the inter-annotator agreement on the whole annotation sequence CV U goes up to 0.78 and 0.83. Then, an automatic method using CFRs is exploited for creating a supervised model for the recognition of these categories. The obtained F-measure is 0.60 for C, 0.82 for V, and 0.76 for U.
引用
收藏
页码:203 / 208
页数:6
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