Espinosa-Anke L, Tello J, Pardo A, Medrano I, Ureña A, Salcedo I, Saggion H. Savana: A Global Information Extraction and Terminology Expansion Framework in the Medical Domain. Procesamiento del Lenguaje Natural 57: 23-30 (2016)
We develop a large number of software tools and hosting infrastructures to support the research developed at the Department. We will be detailing in this section the different tools available. You can take a look for the moment at the offer available within the UPF Knowledge Portal, the innovations created in the context of EU projects in the Innovation Radar and the software sections of some of our research groups:
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Artificial Intelligence |
Nonlinear Time Series Analysis |
Web Research |
Music Technology |
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Interactive Technologies |
Barcelona MedTech |
Natural Language Processing |
Nonlinear Time Series Analysis |
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UbicaLab |
Wireless Networking |
Educational Technologies |
Espinosa-Anke L, Tello J, Pardo A, Medrano I, Ureña A, Salcedo I, Saggion H. Savana: A Global Information Extraction and Terminology Expansion Framework in the Medical Domain. Procesamiento del Lenguaje Natural 57: 23-30 (2016)
Espinosa-Anke L, Tello J, Pardo A, Medrano I, Ureña A, Salcedo I, Saggion H. Savana: A Global Information Extraction and Terminology Expansion Framework in the Medical Domain. Procesamiento del Lenguaje Natural 57: 23-30 (2016) - Chapter 6.4
Terminological databases constitute a fundamental source of information in the medical domain. They are used daily both by practitioners in the area, as well as in academia. Several resources of this kind are available, e.g. CIE, SnomedCT or UMLS (Unified Medical Language System). These terminological databases are of high quality due to them being the result of collaborative expert knowledge. However, they may show certain drawbacks in terms of faithfully representing the ever-changing medical domain. Therefore, systems aimed at capturing novel terminological knowledge in heterogeneous text sources, and able to include them in standard terminologies have the potential to add great value to such repositories. This paper presents, first, Savana, a Biomedical Information Extraction system which, combined with a validation phase carried out by medical practitioners, is used to populate the Spanish branch of SnomedCT with novel knowledge. Second, we describe and evaluate a system which, given a novel medical term, finds its most likely hypernym, thus becoming an enabler in the task of terminological database enrichment and expansion.