es:DETección automática de Efectos Adversos a Medicamentos en Informes médicos usando tecnologías de procesamiento del lenguaje natural
eu:Sendagaien aurkako erreakzioen detekzioa txosten medikuetan, lengoaia naturalaren prozesamenduko teknikak erabiliz.
en:Automatic Detection of Adverse Drug Reactions in Medical Records using Natural Language Processing Technologies
This project aims at the application of generic Natural Language Processing (NLP) tools to the processing of medical records of the clinical digital history, in the form of patient discharge records, evolutive records and other types of medical documents, in order to detect adverse drug reactions. The information processed in Health systems is based mainly on language and, for that reason, NLP techniques can give way to many innovative applications as they will allow to efficiently analyze and structure the text contents, easing the processing and interpretation of the documents.
The main objective of this project is to develop a prototype to empirically validate the information extraction process applied to the detection of adverse drug reactions. Specifically, the project will make use of the texts provided by the Pharmacology Service of the Galdakao-Usansolo Hospital (HGU) and University Hospital of Basurto (HUB). These hospitals can be considered the "clients", and will provide both the texts and the final user feedback, and constitute a central point of the project. They will provide the texts and the material the project will work with, as well as the expeience of the final user. Moreover, the pharmacology assessment of the HGU and HUB services will also give us the expert's knowledge needed in the project. The Pharmacovigilance Unit of the Basque Autonomous Community is also located at HGU, an essential partner in this project.
IXA Group - EHU-UPV
Visitor: Andrea Horbach, Automatic scoring 2019-Sep-20
One of the best three papers on Clinical NLP in 2017 was published by Ixa Group 2019-Jun-28
Mitxelena Award for PhD theses 2018 to Olatz Perez-de-Viñaspre: Automatic medical term generation 2019-May-24
Eneko Agirre awarded by Google Research 2019-May-24
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