The Adverse Drug Reactions From Patient Reports in Social Media Project: Protocol for an Evaluation Against a Gold Standard

Autor: Rim Aboukhamis, Anita Burgun, Badisse Dahamna, Pierre Karapetiantz, Xiaoyi Chen, Nathalie Texier, Agnès Lillo-Le Louët, Carole Faviez, Yannick Girardeau, Sylvie Guillemin-Lanne, Myrtille Deldossi, Armelle Arnoux-Guenegou, Sandrine Katsahian

Publikováno v: JMIR Research Protocols
JMIR Research Protocols, JMIR publications, 2019, 8 (5), pp.e11448. ⟨10.2196/11448⟩

Background: Social media is a potential source of information on postmarketing drug safety surveillance that still remains unexploited nowadays. Information technology solutions aiming at extracting adverse reactions (ADRs) from posts on health forum

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2480c0081f5e67d8ace0dca8494212f7
http://europepmc.org/articles/PMC6528435

Mining Adverse Drug Reactions in Social Media with Named Entity Recognition and Semantic Methods

Autor: Xiaoyi Chen, Myrtille Deldossi, Rim Aboukhamis, Carole Faviez, Badisse Dahamna, Pierre Karapetiantz, Armelle Guenegou-Arnoux, Yannick Girardeau, Sylvie Guillemin-Lanne, Agnès Lillo-Le-Louët, Nathalie Texier, Anita Burgun, Sandrine Katsahian

Publikováno v: Studies in Health Technology and Informatics
Studies in Health Technology and Informatics, IOS Press, 2017, 245, pp.322-326
HAL

International audience; Suspected adverse drug reactions (ADR) reported by patients through social media can be a complementary source to current pharmacovigilance systems. However, the performance of text mining tools applied to social media text da

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::b067a1e73d39fde3895d3380d945cd00
https://hal.archives-ouvertes.fr/hal-03251581

Spontaneous speech and opinion detection: mining call-centre transcripts

Autor: Ariane Cavet, Anne-Laure Daquo, Chloé Clavel, Sandrine Courcinous, Sylvie Guillemin-Lanne, Frederik Cailliau, Martine Garnier-Rizet, Charlotte Danesi, Marjorie Seizou, Myrtille Deldossi, Gilles Adda, Géraldine Chapuis, Philippe Suignard

Publikováno v: Language Resources and Evaluation. 47:1089-1125

Opinion mining on conversational telephone speech tackles two challenges: the robustness of speech transcriptions and the relevance of opinion models. The two challenges are critical in an industrial context such as marketing. The paper addresses joi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4e7cd17bb56da9fef8c75bffe44f812a
https://doi.org/10.1007/s10579-013-9224-5

CallSurf: search by content, navigation and knowledge extraction on call center conversational speech, for marketing and strategic intelligence

Autor: Martine Garnier-Rizet, Sylvie Guillemin-Lanne, Frederik Cailliau

Publikováno v: HAL

In this paper, we describe a solution implemented to analyze automatically call center conversations and find out the underlying reasons for customer calls. The CALLSURF solution aims at improving sales and marketing effectiveness as well as call cen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::899d4ae677b88312f63a1a77bc797a62
https://hal.archives-ouvertes.fr/hal-00716078

CallSurf - Automatic transcription, indexing and structuration of call center conversational speech for knowledge extraction and query by content

Autor: Martine Garnier-Rizet, Gilles Adda, Frederik Cailliau, Jean-Luc Gauvain, Sylvie Guillemin-Lanne, Lori Lamel, Stephan Vanni, Claire Waast-Richard

Publikováno v: Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
Sixth International Conference on Language Resources and Evaluation (LREC'08)
Sixth International Conference on Language Resources and Evaluation (LREC'08), May 2008, Marrakech, Morocco. pp.2623-2628
HAL

International audience; Being the client's first interface, call centres worldwide contain a huge amount of information of all kind under the form of conversational speech. If accessible, this information can be used to detect eg. major events and or

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::232edacd36a1c7de71c12f2fe69f3e24
https://hal.science/hal-00716016