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SemClinBr - a multi-institutional and multi-specialty semantically annotated corpus for Portuguese clinical NLP tasks.

Authors :
Oliveira, Lucas Emanuel Silva e
Peters, Ana Carolina
da Silva, Adalniza Moura Pucca
Gebeluca, Caroline Pilatti
Gumiel, Yohan Bonescki
Cintho, Lilian Mie Mukai
Carvalho, Deborah Ribeiro
Al Hasan, Sadid
Moro, Claudia Maria Cabral
Source :
Journal of Biomedical Semantics. 5/8/2022, Vol. 13 Issue 1, p1-19. 19p.
Publication Year :
2022

Abstract

Background: The high volume of research focusing on extracting patient information from electronic health records (EHRs) has led to an increase in the demand for annotated corpora, which are a precious resource for both the development and evaluation of natural language processing (NLP) algorithms. The absence of a multipurpose clinical corpus outside the scope of the English language, especially in Brazilian Portuguese, is glaring and severely impacts scientific progress in the biomedical NLP field. Methods: In this study, a semantically annotated corpus was developed using clinical text from multiple medical specialties, document types, and institutions. In addition, we present, (1) a survey listing common aspects, differences, and lessons learned from previous research, (2) a fine-grained annotation schema that can be replicated to guide other annotation initiatives, (3) a web-based annotation tool focusing on an annotation suggestion feature, and (4) both intrinsic and extrinsic evaluation of the annotations. Results: This study resulted in SemClinBr, a corpus that has 1000 clinical notes, labeled with 65,117 entities and 11,263 relations. In addition, both negation cues and medical abbreviation dictionaries were generated from the annotations. The average annotator agreement score varied from 0.71 (applying strict match) to 0.92 (considering a relaxed match) while accepting partial overlaps and hierarchically related semantic types. The extrinsic evaluation, when applying the corpus to two downstream NLP tasks, demonstrated the reliability and usefulness of annotations, with the systems achieving results that were consistent with the agreement scores. Conclusion: The SemClinBr corpus and other resources produced in this work can support clinical NLP studies, providing a common development and evaluation resource for the research community, boosting the utilization of EHRs in both clinical practice and biomedical research. To the best of our knowledge, SemClinBr is the first available Portuguese clinical corpus. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20411480
Volume :
13
Issue :
1
Database :
Academic Search Index
Journal :
Journal of Biomedical Semantics
Publication Type :
Academic Journal
Accession number :
156748762
Full Text :
https://doi.org/10.1186/s13326-022-00269-1