Name
Abstract | ||
|---|---|---|
Data quality plays a very important role in predicting clinical outcomes. Data quality is multi dimensional and most relevant studies consider just one or two dimensions. In this study a systematic data quality assessment is performed using four data dimensions. The results demonstrate that performance of predictive models improves when the quality of the data is assessed and addressed systematically. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.3233/978-1-61499-564-7-1069 | Studies in Health Technology and Informatics |
Keywords | Field | DocType |
predictive modeling,data quality assessment,data preprocessing | Data science,Data mining,Text mining,Multi dimensional,Data quality,Information retrieval,Computer science | Conference |
Volume | ISSN | Citations |
216 | 0926-9630 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jitendra Jonnagaddala | 1 | 46 | 10.28 |
| Siaw-Teng Liaw | 2 | 57 | 13.79 |
| Pradeep Ray | 3 | 51 | 6.42 |