Name
Abstract | ||
|---|---|---|
The aim of this study is to predict, through data mining tools, the incidence of perineal tear. This kind of laceration developed during child delivery might imply surgery and entails a set of several consequences. Clinical Decision Support Systems, with the information collected from patients’ electronic health records combined with the data mining techniques, may decrease the incidence of perineal tears during labour. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.procs.2017.08.284 | Procedia Computer Science |
Keywords | Field | DocType |
Data Mining,Obstetrics,Perineal Tear,Decision Support Systems | Computer science,Decision support system,Artificial intelligence,Medical emergency,Clinical decision support system,Perineal tear,Machine learning | Conference |
Volume | ISSN | Citations |
113 | 1877-0509 | 0 |
PageRank | References | Authors |
0.34 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francisca Fonseca | 1 | 0 | 1.01 |
| Hugo Peixoto | 2 | 18 | 9.54 |
| Filipe Miranda | 3 | 0 | 1.01 |
| José Machado | 4 | 83 | 32.46 |
| António Abelha | 5 | 243 | 57.30 |