Exploring deep learning methods for recognizing rare diseases and their clinical manifestations from texts

Autor: Isabel Segura-Bedmar, David Camino-Perdones, Sara Guerrero-Aspizua

Publikováno v: BMC Bioinformatics, Vol 23, Iss 1, Pp 1-23 (2022)

Abstract Background and objective Although rare diseases are characterized by low prevalence, approximately 400 million people are affected by a rare disease. The early and accurate diagnosis of these conditions is a major challenge for general pract

Externí odkaz: https://doaj.org/article/a7b7b5146fc24c1ea630b534ee63ea2f

Evaluation of pooling operations in convolutional architectures for drug-drug interaction extraction

Autor: Víctor Suárez-Paniagua, Isabel Segura-Bedmar

Publikováno v: BMC Bioinformatics, Vol 19, Iss S8, Pp 39-47 (2018)

Abstract Background Deep Neural Networks (DNN), in particular, Convolutional Neural Networks (CNN), has recently achieved state-of-art results for the task of Drug-Drug Interaction (DDI) extraction. Most CNN architectures incorporate a pooling layer

Externí odkaz: https://doaj.org/article/dba792d88a2843b1b309771fc836fc90

Simplifying drug package leaflets written in Spanish by using word embedding

Autor: Isabel Segura-Bedmar, Paloma Martínez

Publikováno v: Journal of Biomedical Semantics, Vol 8, Iss 1, Pp 1-9 (2017)

Abstract Background Drug Package Leaflets (DPLs) provide information for patients on how to safely use medicines. Pharmaceutical companies are responsible for producing these documents. However, several studies have shown that patients usually have p

Externí odkaz: https://doaj.org/article/55f971810ee64701be33a0fa75b88006

Cohort selection for clinical trials using deep learning models

Autor: Isabel Segura-Bedmar, Pablo Raez

Publikováno v: e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
Journal of the American Medical Informatics Association : JAMIA
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname

Objective The goal of the 2018 n2c2 shared task on cohort selection for clinical trials (track 1) is to identify which patients meet the selection criteria for clinical trials. Cohort selection is a particularly demanding task to which natural langua

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::df7f9e30d089dea08e10f242c531dddb
https://doi.org/10.1093/jamia/ocz139

Predicting of anaphylaxis in big data EMR by exploring machine learning approaches

Autor: Cristóbal Colón-Ruiz, Miguel A. Tejedor-Alonso, Isabel Segura-Bedmar, Mar Moro-Moro

Publikováno v: Journal of Biomedical Informatics. 87:50-59

Anaphylaxis is a life-threatening allergic reaction that occurs suddenly after contact with an allergen. Epidemiological studies about anaphylaxis are very important in planning and evaluating new strategies that prevent this reaction, but also in pr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a492a671e50719bf49507626dc199083
https://doi.org/10.1016/j.jbi.2018.09.012