Cousyn Charles, Bouchard Kévin, Gaboury Sébastien et Bouchard Bruno. (2020). Towards using scientific publications to automatically extract information on rare diseases. Mobile Networks and Applications, 25, (3), p. 953-960.
Le texte intégral n'est pas disponible pour ce document.
URL officielle: http://dx.doi.org/doi:10.1007/s11036-019-01237-3
Résumé
A small percentage of the population is afflicted by what is called an orphan or a rare disease. All over the world, there are about several thousand of these diseases. When adding up together all the individuals who are affected, it amounts for up to 10% of the US population. Scientific works on these diseases are often poorly financed due to the lack of potential markets for a treatment, which means for patients and clinicians a very limited and scattered access to vital information. To contribute addressing this issue, we present in this paper a new software tool for automating the extraction of information related to rare diseases from scientific publications. More precisely, our contribution consists in a new method of extracting automatically symptoms of these diseases from research papers exploiting a Named Entity Recognition (NER) algorithm based on the numerical statistic Term Frequency - Inverse Document Frequency (TF-IDF). The proposed tool has been tested using PubMed Central (PMC) database.
Type de document: | Article publié dans une revue avec comité d'évaluation |
---|---|
ISSN: | 1383-469X |
Volume: | 25 |
Numéro: | 3 |
Pages: | p. 953-960 |
Version évaluée par les pairs: | Oui |
Date: | 2020 |
Identifiant unique: | 10.1007/s11036-019-01237-3 |
Sujets: | Sciences naturelles et génie > Sciences mathématiques > Informatique Sciences de la santé > Sciences médicales > Épidémiologie et biostatistique |
Département, module, service et unité de recherche: | Départements et modules > Département d'informatique et de mathématique |
Mots-clés: | text mining, rare disease, named entity recognition, knowledge aggregation, symptoms |
Déposé le: | 10 févr. 2021 20:02 |
---|---|
Dernière modification: | 10 févr. 2021 20:02 |
Éditer le document (administrateurs uniquement)