The aim of this project is to define and develop information extraction and retrieval techniques based on texts from the medical domain. This will be carried out following two basic tasks: firstly, processing scientific documents in English about pharmacology, and secondly, processing informative texts about health topics in other languages such as Spanish and Arabic.

The aim is to research in technology based on automatic language processing for information location and retrieval from medical texts and other resources (reports, electronic medical records, scientific documentation, etc..) specially in Spanish language. Thus, we worked in browsers with different levels of complexity that integrate medical domain-specific resources and terminology (UMLS, SNOMED, etc.) and with different treatment of syntactic and semantic levels.

MAVIR Consortium is a research network co-funded by the Regional Government of Madrid under the IV Plan Regional de Investigación Científica e Innovación Tecnológica (IV PRICIT) integrating a multi-disciplinar team made of scientists, engineers, linguists and documentalists working together on two main areas:Human Language Technologies and Scientific Communication via WWW. The thematic network suggested includes 25 doctors organised in 6 research groups (UNED, UAM, UC3M, UEM, UPM and CINDOC) of the CM that from a multi-discipline perspective complement in various dimensions: academic vs.

BRAVO is devoted to research on technologies to improve the answers search in both text and voice, and the main result is a platform for a modular answers search system which allows to measure the improvement of different techniques for questions classification, answer extraction, passages retrieval, etc. SPINDEL is one of the techniques developed in this project, an entity recognizer which, regardless of language, applies machine learning based on bootstrapping.