| Comparing deep learning architectures for sentiment analysis on drug reviews | 4 | 0.42 | 2020 |
| Lexical simplification approach to support the accessibility guidelines | 0 | 0.34 | 2019 |
| A two-stage deep learning approach for extracting entities and relationships from medical texts. | 0 | 0.34 | 2019 |
| Análisis de sentimiento en el dominio salud: analizando comentarios sobre fármacos. | 1 | 0.35 | 2019 |
| Cohort selection for clinical trials using deep learning models. | 1 | 0.35 | 2019 |
| Hulat-TaskAB at eHealth-KD Challenge 2019 - Knowledge Recognition from Health Documents by BiLSTM-CRF. | 0 | 0.34 | 2019 |
| Protected Health Information Recognition by BiLSTM-CRF. | 0 | 0.34 | 2019 |
| Lexical simplification approach using easy-to-read resources. | 0 | 0.34 | 2019 |
| Early Risk Prediction by means of DeepLearning. | 0 | 0.34 | 2019 |
| LABDA's Early Steps Toward Multimodal Stance Detection. | 0 | 0.34 | 2018 |
| Evaluation of pooling operations in convolutional architectures for drug-drug interaction extraction. | 1 | 0.43 | 2018 |
| UC3M-NII Team at SemEval-2018 Task 7: Semantic Relation Classification in Scientific Papers via Convolutional Neural Network. | 0 | 0.34 | 2018 |
| Predicting of anaphylaxis in big data EMR by exploring machine learning approaches. | 0 | 0.34 | 2018 |
| A Hybrid Bi-LSTM-CRF Model to Recognition of Disabilities from Biomedical Texts. | 0 | 0.34 | 2018 |
| A Hybrid Bi-LSTM-CRF model for Knowledge Recognition from eHealth documents. | 0 | 0.34 | 2018 |
| LABDA at TASS-2018 Task 3: Convolutional Neural Networks for Relation Classification in Spanish eHealth documents. | 0 | 0.34 | 2018 |
| MC-UC3M Participation at TAC 2017 Adverse Drug Reaction Extraction from Drug Labels. | 0 | 0.34 | 2017 |
| Exploring convolutional neural networks for drug-drug interaction extraction. | 3 | 0.39 | 2017 |
| Exploring Convolutional Neural Networks for Sentiment Analysis of Spanish tweets. | 3 | 0.37 | 2017 |
| LABDA at SemEval-2017 Task 10: Relation Classification between keyphrases via Convolutional Neural Network. | 0 | 0.34 | 2017 |
| Simplifying drug package leaflets written in Spanish by using word embedding. | 0 | 0.34 | 2017 |
| LABDA at SemEval-2017 Task 10: Extracting Keyphrases from Scientific Publications by combining the BANNER tool and the UMLS Semantic Network. | 0 | 0.34 | 2017 |
| Turning user generated health-related content into actionable knowledge through text analytics services | 5 | 0.38 | 2016 |
| Using Recursive Neural Networks to Detect and Classify Drug-Drug Interactions from Biomedical Texts. | 0 | 0.34 | 2016 |
| EasyLecto: Un sistema de simplificación léxica de efectos adversos presentes en prospectos de fármacos en español. | 0 | 0.34 | 2016 |
| Simplifying Drug Package Leaflets. | 1 | 0.35 | 2016 |
| Conceptual models of drug-drug interactions: A summary of recent efforts. | 3 | 0.40 | 2016 |
| LABDA at the 2016 TASS Challenge Task: Using Word Embeddings for the Sentiment Analysis Task. | 1 | 0.35 | 2016 |
| DINTO: Using OWL Ontologies and SWRL Rules to Infer Drug-Drug Interactions and Their Mechanisms. | 11 | 0.60 | 2015 |
| Exploring language technologies to provide support to WCAG 2.0 and E2R guidelines | 0 | 0.34 | 2015 |
| Exploring Spanish health social media for detecting drug effects | 13 | 0.55 | 2015 |
| The CHEMDNER corpus of chemicals and drugs and its annotation principles | 72 | 2.17 | 2015 |
| Pharmacovigilance through the Development of Text Mining and Natural Language Processing Techniques. | 5 | 0.41 | 2015 |
| Exploring Word Embedding for Drug Name Recognition | 8 | 0.60 | 2015 |
| Application of Domain Ontologies to Natural Language Processing: A Case Study for Drug-Drug Interactions | 2 | 0.37 | 2015 |
| Trendminer: Large-Scale Cross-Lingual Trend Mining Summarization Of Real-Time Media Streams | 0 | 0.34 | 2014 |
| Extracting drug indications and adverse drug reactions from Spanish health social media | 10 | 0.53 | 2014 |
| Adrspanishtool: A Tool For Extracting Adverse Drug Reactions And Indications | 0 | 0.34 | 2014 |
| Detecting drugs and adverse events from Spanish social media streams | 17 | 0.78 | 2014 |
| Lessons learnt from the DDIExtraction-2013 Shared Task. | 30 | 1.09 | 2014 |
| SemEval-2013 Task 9 : Extraction of Drug-Drug Interactions from Biomedical Texts (DDIExtraction 2013) | 45 | 1.29 | 2013 |
| Combining dictionaries and ontologies for drug name recognition in biomedical texts | 4 | 0.40 | 2013 |
| Lightly supervised acquisition of named entities and linguistic patterns for multilingual text mining. | 5 | 0.41 | 2013 |
| An Ontology for Drug-drug Interactions. | 2 | 0.42 | 2013 |
| A Web Prototype for Detecting Chemical Compounds and Drugs. | 0 | 0.34 | 2013 |
| The DDI corpus: an annotated corpus with pharmacological substances and drug-drug interactions. | 40 | 1.54 | 2013 |
| Prototipo buscador de información médica en corpus multilingües y extractor de información sobre fármacos. | 0 | 0.34 | 2012 |
| DDIExtractor: a web-based java tool for extracting drug-drug interactions from biomedical texts | 1 | 0.34 | 2011 |
| Using a shallow linguistic kernel for drug-drug interaction extraction. | 51 | 2.02 | 2011 |
| A linguistic rule-based approach to extract drug-drug interactions from pharmacological documents. | 30 | 0.82 | 2011 |
