es:EXTracción de RElaciones entre Conceptos Médicos en fuentes de información heterogéneas
eu:Kontzeptu medikoen arteko erlazioen erauzketa askotariko informazio-iturrietatik
en:Extracting Relations among Medical Concepts from Heteregenous Information Sources
The main challenge is to address the generation of techniques and tools to allow efficient and reliable access to vast amounts of information which currently are manually accessed by health care professionals. The volume of information that health professionals use in their daily task is enormous and it is growing. We believe that, in addition, the information contained in the web of specialized pages and/or social networks can provide medical content of different types based on the experience of patients. It is important that these professionals have mechanisms to facilitate an "advanced access" to information contained in these millions of documents of heterogeneous nature. By "advanced access" we mean access focusing on the concept and retrieval of the related medical information present in different documents and heterogeneous information sources.
The project has a multidisciplinary nature and will be addressed through collaboration between research groups expert in information technology and professionals in the health area. This collaboration can help to create synergies between the two parties.
The groups involved in the project are:
IXA Group - EHU-UPV
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
PhD Thesis: Computational Model for Semantic Textual Similarity (I. San Vicente, 2019/03/11) 2019-Mar-12
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