Time to kick-start text mining for biomaterials
The rapidly expanding biomaterials data are challenging to organize. Text mining systems are powerful tools that automatically extract and integrate information in large textual collections. As text mining leaps forward by leveraging deep-learning approaches, it is time to address the most pressing...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/192371 |
| Acceso en línea: | https://hdl.handle.net/2117/192371 https://dx.doi.org/10.1038/s41578-020-0215-z |
| Access Level: | acceso abierto |
| Palabra clave: | Machine learning Biomedical materials Data mining Aprenentatge automàtic Materials biomèdics Mineria de dades Àrees temàtiques de la UPC::Enginyeria biomèdica::Biomaterials |
| Sumario: | The rapidly expanding biomaterials data are challenging to organize. Text mining systems are powerful tools that automatically extract and integrate information in large textual collections. As text mining leaps forward by leveraging deep-learning approaches, it is time to address the most pressing biomaterials information and data processing needs. |
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