| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560383 |
| ISSN: | 1405-5546 |
| Autores: | Minh, Hiep Nguyen1 Thi Minh, Huyen Nguyen2 The, Quyen Ngo2 |
| Instituciones: | 1Dalat University, Da Lat. Vietnam 2VNU University of Science, Ha Noi. Vietnam |
| Año: | 2018 |
| Periodo: | Oct-Dic |
| Volumen: | 22 |
| Número: | 4 |
| Paginación: | 1287-1294 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | Clinical texts contain textual data recorded by doctors during medical examinations. Sentences in clinical texts are generally short, narrative, not strictly adhering to Vietnamese grammar and contain many medical terms which are not present in general dictionaries. In this paper, we investigate the tasks of lexical analysis and phrase chunking for Vietnamese clinical texts. Although there exist several tools for general Vietnamese text analysis, these tools showed a limited quality in the clinical domain due to the specific grammatical style of clinical texts and the lack of medical vocabulary. Our main contributions are the construction of an annotated corpus (vnEMR) and lexical resources in the medical domain and in consequence the improvement of the quality of the tools for clinical text analysis, including word segmentation, part-of-speech tagging and chunking. |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial |
| Keyword: | Chunking, Clinical text, Collocation, Lexical resources, Medical vocabulary, POS tagging, VnEMR, Word segmentation, Artificial intelligence |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
