| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4943597 | Expert Systems with Applications | 2017 | 18 Pages |
Abstract
DSScreening has been tested by comparing its predictions with the results of 152 real analyses from two groups: (1) NS samples and (2) clinical samples belonging to individuals of all ages with symptoms that do not necessarily correspond to an IEM. The system has reduced the time needed by 98.7% when compared to the interpretation time spent by laboratory professionals. Besides, it has correctly classified 100% of the NS samples and obtained an accuracy of 70% for samples belonging to individuals with clinical symptoms.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Unai Segundo, Luis Aldámiz-EchevarrÃa, Javier López-Cuadrado, David Buenestado, Fernando Andrade, Tomás A. Pérez, Raúl Barrena, Eduardo G. Pérez-Yarza, Juan M. Pikatza,