Name
Abstract | ||
|---|---|---|
The large amount of medical information available through the Internet, in both structure and text formats, makes that different types of users will encounter different problems when they have to carry out an effective search. On the one hand, medical students, health staff and researchers in the field of biomedicine have a variety of sources and tools of different characteristics which require a learning period sometimes insurmountable. On the other hand, patients, family members and people outside of the medical profession, face the added problem of not being sufficiently familiarized with medical terminology. In this paper we present a tool that can extract relevant medical concepts present in a clinical text, using techniques for named entity recognition, applied on lists of concepts, and annotation techniques from ontologies. To propose these concepts, our tool makes use of a non formal knowledge source, such as Freebase, and formal resources such as MedlinePlus and PubMed. We argue that the combination of these resources, with information less formal and more plain language (like Freebase), with formal information and more plain language (like Medlineplus) or with formal information and more technical language (such as the Pubmed scientific literature), optimize the process of discover medical information on a complex clinical case to users with different profiles and needs, such as are patients, doctors or researchers. Our ultimate goal is to build a platform to accommodate different techniques facilitating the practice of translational medicine. |
Year | Venue | Keywords |
|---|---|---|
2011 | PROCESAMIENTO DEL LENGUAJE NATURAL | Bioinformatics, translational medicine, ontologies, NER, information retrieval, case-based learning |
DocType | Volume | Issue |
Journal | 46 | 46 |
ISSN | Citations | PageRank |
1135-5948 | 2 | 0.47 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| fernando soto aparicio | 1 | 2 | 0.47 |
| Manuel De Buenaga Rodríguez | 2 | 67 | 16.59 |
| Margarita Rubio | 3 | 11 | 2.27 |
| maria asuncion hernando | 4 | 11 | 1.93 |
| Diego Gachet | 5 | 28 | 6.28 |
| Enrique Puertas Sanz | 6 | 175 | 16.60 |
| J. Ignacio Giráldez | 7 | 13 | 3.44 |