Name
Title | ||
|---|---|---|
Nomographic representation of logistic regression models: a case study using patient self-assessment data. |
Abstract | ||
|---|---|---|
Logistic regression models are widely used in medicine, but difficult to apply without the aid of electronic devices. In this paper, we present a novel approach to represent logistic regression models as nomograms that can be evaluated by simple line drawings. As a case study, we show how data obtained from a questionnaire-based patient self-assessment study on the risks of developing melanoma can be used to first identify a subset of significant covariates, build a logistic regression model, and finally transform the model to a graphical format. The advantage of the nomogram is that it can easily be mass-produced, distributed and evaluated, while providing the same information as the logistic regression model it represents. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1016/j.jbi.2005.02.006 | Journal of Biomedical Informatics |
Keywords | Field | DocType |
electronic device,logistic regression model,significant covariates,patient self-assessment,nomogram,case study,questionnaire-based patient self-assessment study,graphical format,simple line drawing,nomographic representation,nomographic decision aid,patient self-assessment data,novel approach | Data mining,Self-assessment,Covariate,Nomogram,Multinomial logistic regression,Computer science,Logistic model tree,Statistics,Logistic regression,Line drawings | Journal |
Volume | Issue | ISSN |
38 | 5 | 1532-0464 |
Citations | PageRank | References |
4 | 0.66 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stephan Dreiseitl | 1 | 338 | 34.80 |
| Alexandra Harbauer | 2 | 4 | 0.66 |
| Michael Binder | 3 | 4 | 0.66 |
| Harald Kittler | 4 | 148 | 11.46 |