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)
List of results published directly linked with the projects co-funded by the Spanish Ministry of Economy and Competitiveness under the María de Maeztu Units of Excellence Program (MDM-2015-0502).
List of publications acknowledging the funding in Scopus.
The record for each publication will include access to postprints (following the Open Access policy of the program), as well as datasets and software used. Ongoing work with UPF Library and Informatics will improve the interface and automation of the retrieval of this information soon.
The MdM Strategic Research Program has its own community in Zenodo for material available in this repository 
as well as at the UPF e-repository 
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.