ITEXT-BIO: Intelligent Term EXTraction for BIOmedical analysis

Kafando Rodrique, Decoupes Rémy, Valentin Sarah, Sautot Lucile, Teisseire Maguelonne, Roche Mathieu. 2021. ITEXT-BIO: Intelligent Term EXTraction for BIOmedical analysis. Health Information Science and Systems, 9:29, 23 p.

https://doi.org/10.1007/s13755-021-00156-6

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Quartile : Q2, Sujet : MEDICAL INFORMATICS

Résumé : Here, we introduce ITEXT-BIO, an intelligent process for biomedical domain terminology extraction from textual documents and subsequent analysis. The proposed methodology consists of two complementary approaches, including free and driven term extraction. The first is based on term extraction with statistical measures, while the second considers morphosyntactic variation rules to extract term variants from the corpus. The combination of two term extraction and analysis strategies is the keystone of ITEXT-BIO. These include combined intra-corpus strategies that enable term extraction and analysis either from a single corpus (intra), or from corpora (inter). We assessed the two approaches, the corpus or corpora to be analysed and the type of statistical measures used. Our experimental findings revealed that the proposed methodology could be used: (1) to efficiently extract representative, discriminant and new terms from a given corpus or corpora, and (2) to provide quantitative and qualitative analyses on these terms regarding the study domain.

Mots-clés Agrovoc : fouille de textes, terminologie, sciences médicales, covid-19

Mots-clés libres : Text mining, Terminlology extraction, Biomedical terminology, Intelligent system, COVID-19

Classification Agris : S50 - Santé humaine
C30 - Documentation et information
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 4 (2019-) - Santé des plantes, des animaux et des écosystèmes

Agences de financement européennes : European Commission

Projets sur financement : (EU) MOnitoring Outbreak events for Disease surveillance in a data science context

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