| Téléchargement | - Voir la version finale : The importance of sharing patient-generated clinical speech and language data (PDF, 317 Kio)
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| DOI | Trouver le DOI : https://doi.org/10.18653/v1/W19-3007 |
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| Auteur | Rechercher : Fraser, Kathleen C.1; Rechercher : Linz, Nicklas; Rechercher : Lindsay, Hali; Rechercher : König, Alexandra |
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| Affiliation | - Conseil national de recherches du Canada. Technologies numériques
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| Format | Texte, Article |
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| Conférence | Sixth Workshop on Computational Linguistics and Clinical Psychology, June 6, 2019, Minneapolis, Minnesota, United States |
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| Résumé | Increased access to large datasets has driven progress in NLP. However, most computational studies of clinically-validated, patient-generated speech and language involve very few datapoints, as such data are difficult (and expensive) to collect. In this position paper, we argue that we must find ways to promote data sharing across research groups, in order to build datasets of a more appropriate size for NLP and machine learning analysis. We review the benefits and challenges of sharing clinical language data, and suggest several concrete actions by both clinical and NLP researchers to encourage multi-site and multi-disciplinary data sharing. We also propose the creation of a collaborative data sharing platform, to allow NLP researchers to take a more active responsibility for data transcription, annotation, and curation. |
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| Date de publication | 2019-06-06 |
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| Maison d’édition | Association for Computational Linguistics |
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| Licence | |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | 7344515b-78fb-4d26-a038-8bd29be8c398 |
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| Enregistrement créé | 2021-08-23 |
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| Enregistrement modifié | 2021-08-24 |
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