From: Determine the therapeutic role of radiotherapy in administrative data: a data mining approach
Model | Classification variables | Number of rules | Accuracy (CI) | Confusion matrix | |
---|---|---|---|---|---|
Model 1 | Fraction-size | 10 | 94.6% (94.4%, 94.7%) | C to P*: | 2.2% |
Disease site | P to C: | 3.3% | |||
Body-region | |||||
Time from the 1st treatment | |||||
Model 2 | Fraction-size | 13 | 94.5% (94.3%, 94.6%) | C to P: | 1.9% |
Body-region | P to C: | 3.6% | |||
Time from the 1st treatment | |||||
Model 3 | Fraction-size | 10 | 94.2% (94.0%, 94.3%) | C to P: | 2.4% |
Disease site | P to C: | 3.4% | |||
Time from the 1st treatment | |||||
Model 4 | Fraction-size | 8 | 94.1% (94.0%, 94.3%) | C to P: | 2.0% |
Time from the 1st treatment | P to C: | 3.8% | |||
Model 5 | Disease site | 18 | 92.0% (91.8%, 92.2%) | C to P: | 3.0% |
Body-region | P to C: | 4.9% | |||
Time from the 1st treatment | |||||
Model 6 | Body-region | 11 | 91.0% (90.8%, 91.2%) | C to P: | 2.4% |
Time from the 1st treatment | P to C: | 6.6% | |||
Model 7 | Disease site | 10 | 90.1% (89.9%, 90.3%) | C to P: | 3.8% |
Time from the 1st treatment | P to C: | 6.2% |