Name
Title | ||
|---|---|---|
The Aid Of Machine Learning To Overcome The Classification Of Real Health Discharge Reports Written In Spanish |
Abstract | ||
|---|---|---|
Hospitals attached to the Spanish Ministry of Health are currently using the International Classification of Diseases 9 Clinical Modification (ICD9-CM) to classify health discharge records. Nowadays, this work is manually done by experts. This paper tackles the automatic classification of real Discharge Records in Spanish following the ICD9-CM standard. The challenge is that the Discharge Records are written in spontaneous language. We explore several machine learning techniques to deal with the classification problem. Random Forest resulted in the most competitive one, achieving an F-measure of 0.876. |
Year | Venue | Keywords |
|---|---|---|
2014 | PROCESAMIENTO DEL LENGUAJE NATURAL | Natural Language Processing, Biomedicine, Machine Learning |
DocType | Volume | Issue |
Journal | 53 | 53 |
ISSN | Citations | PageRank |
1135-5948 | 0 | 0.34 |
References | Authors | |
4 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alicia Pérez | 1 | 189 | 31.43 |
| Arantza Casillas | 2 | 105 | 26.01 |
| Koldo Gojenola | 3 | 164 | 26.64 |
| Maite Oronoz | 4 | 82 | 18.92 |
| Nerea Aguirre | 5 | 0 | 0.34 |
| Estibaliz Amillano | 6 | 0 | 0.34 |