Paloma Martínez

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The DDIExtraction 2013 task concerns the recognition of drugs and extraction of drugdrug interactions that appear in biomedical literature. We propose two subtasks for the DDIExtraction 2013 Shared Task challenge: 1) the recognition and classification of drug names and 2) the extraction and classification of their interactions. Both subtasks have been very(More)
A drug-drug interaction (DDI) occurs when one drug influences the level or activity of another drug. The increasing volume of the scientific literature overwhelms health care professionals trying to be kept up-to-date with all published studies on DDI. This paper describes a hybrid linguistic approach to DDI extraction that combines shallow parsing and(More)
A drug-drug interaction (DDI) occurs when one drug influences the level or activity of another drug. Information Extraction (IE) techniques can provide health care professionals with an interesting way to reduce time spent reviewing the literature for potential drug-drug interactions. Nevertheless, no approach has been proposed to the problem of extracting(More)
The management of drug-drug interactions (DDIs) is a critical issue resulting from the overwhelming amount of information available on them. Natural Language Processing (NLP) techniques can provide an interesting way to reduce the time spent by healthcare professionals on reviewing biomedical literature. However, NLP techniques rely mostly on the(More)
Toll-like receptors (TLR) are a group of pattern recognition molecules that play a crucial role in innate immunity. TLR2 recognises a variety of microbial components leading to the development of inflammatory and immune responses. To characterise the expression and functional properties of porcine TLR2 (pTLR2), we have raised a panel of monoclonal(More)
This article presents a system for drug name recognition and classification in biomedical texts. The system combines information obtained by the Unified Medical Language System (UMLS) MetaMap Transfer (MMTx) program and nomenclature rules recommended by the World Health Organization (WHO) International Nonproprietary Names (INNs) Program to identify and(More)
To the best of our knowledge, this is the first work that does drug and adverse event detection from Spanish posts collected from a health social media. First, we created a goldstandard corpus annotated with drugs and adverse events from social media. Then, Textalytics, a multilingual text analysis engine, was applied to identify drugs and possible adverse(More)
Drug-drug interactions are frequently reported in the increasing amount of biomedical literature. Information Extraction (IE) techniques have been devised as a useful instrument to manage this knowledge. Nevertheless, IE at the sentence level has a limited effect because of the frequent references to previous entities in the discourse, a phenomenon known as(More)
The automatic extraction of chemical information from text requires the recognition of chemical entity mentions as one of its key steps. When developing supervised named entity recognition (NER) systems, the availability of a large, manually annotated text corpus is desirable. Furthermore, large corpora permit the robust evaluation and comparison of(More)
Background A drug-drug interaction (DDI) occurs when one drug influences the level or activity of another drug. The detection of drug interactions is an important research area in patient safety since these interactions can become very dangerous and increase health care costs. Although there are different databases supporting health care professionals in(More)