Search Results for author: Martin Krallinger

Found 14 papers, 0 papers with code

The SocialDisNER shared task on detection of disease mentions in health-relevant content from social media: methods, evaluation, guidelines and corpora

no code implementations SMM4H (COLING) 2022 Luis Gasco Sánchez, Darryl Estrada Zavala, Eulàlia Farré-Maduell, Salvador Lima-López, Antonio Miranda-Escalada, Martin Krallinger

We anticipate that the corpus and systems resulting from the SocialDisNER track might further foster health related text mining of social media content in Spanish and inspire disease detection strategies in other languages.

Knowledge Graphs

Overview of the Seventh Social Media Mining for Health Applications (#SMM4H) Shared Tasks at COLING 2022

no code implementations SMM4H (COLING) 2022 Davy Weissenbacher, Juan Banda, Vera Davydova, Darryl Estrada Zavala, Luis Gasco Sánchez, Yao Ge, Yuting Guo, Ari Klein, Martin Krallinger, Mathias Leddin, Arjun Magge, Raul Rodriguez-Esteban, Abeed Sarker, Lucia Schmidt, Elena Tutubalina, Graciela Gonzalez-Hernandez

For the past seven years, the Social Media Mining for Health Applications (#SMM4H) shared tasks have promoted the community-driven development and evaluation of advanced natural language processing systems to detect, extract, and normalize health-related information in public, user-generated content.

Spanish Biomedical Crawled Corpus: A Large, Diverse Dataset for Spanish Biomedical Language Models

no code implementations16 Sep 2021 Casimiro Pio Carrino, Jordi Armengol-Estapé, Ona de Gibert Bonet, Asier Gutiérrez-Fandiño, Aitor Gonzalez-Agirre, Martin Krallinger, Marta Villegas

We introduce CoWeSe (the Corpus Web Salud Espa\~nol), the largest Spanish biomedical corpus to date, consisting of 4. 5GB (about 750M tokens) of clean plain text.

PharmaCoNER: Pharmacological Substances, Compounds and proteins Named Entity Recognition track

no code implementations WS 2019 Aitor Gonzalez-Agirre, Montserrat Marimon, Ander Intxaurrondo, Obdulia Rabal, Marta Villegas, Martin Krallinger

We foresee that the PharmaCoNER annotation guidelines, corpus and participant systems will foster the development of new resources for clinical and biomedical text mining systems of Spanish medical data.

named-entity-recognition Named Entity Recognition +1

BSC Participation in the WMT Translation of Biomedical Abstracts

no code implementations WS 2019 Felipe Soares, Martin Krallinger

This paper describes the machine translation systems developed by the Barcelona Supercomputing (BSC) team for the biomedical translation shared task of WMT19.

Machine Translation Translation

Medical Word Embeddings for Spanish: Development and Evaluation

no code implementations WS 2019 Felipe Soares, Marta Villegas, Aitor Gonzalez-Agirre, Martin Krallinger, Jordi Armengol-Estap{\'e}

We performed intrinsic evaluation with our adapted datasets, as well as extrinsic evaluation with a named entity recognition systems using a baseline embedding of general-domain.

named-entity-recognition Named Entity Recognition +2

BVS Corpus: A Multilingual Parallel Corpus of Biomedical Scientific Texts

no code implementations5 May 2019 Felipe Soares, Martin Krallinger

The BVS database (Health Virtual Library) is a centralized source of biomedical information for Latin America and Carib, created in 1998 and coordinated by BIREME (Biblioteca Regional de Medicina) in agreement with the Pan American Health Organization (OPAS).

Machine Translation Translation

Cannot find the paper you are looking for? You can Submit a new open access paper.