TABLE 2:
The average sensitivity/specificity (sens./spec.) scores of competing algorithms on all datasets. The best results are highlighted in bold and the symbol • indicates that Dropfeature-DNNs obtains a better sensitivity/specificity than the corresponding method regarding a pairwise t-test with a 95% confidence interval.
| Measurement | sens./spec. [%] | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Dataset/Method | DNNs | LASSO-SVM | GBFS-SVM | LASSO-DNNs | GBFS-DNNs | SNMF | CNN | Dropout | DNP | Dropfeature-DNNs |
| ALL | 70.5•/74.6• | 75.2•/78.7• | 76.6•/81.3• | 77.4•/79.8• | 80.2•/84.0• | 87.8/86.4• | 82.3•/83.5• | 85.8•/84.7• | 86.3•/85.7• | 88.6/90.8 |
| GCM | 55.8•/57.3• | 64.6•/70.4• | 71.2•/67.5• | 69.5•/65.7• | 71.3•/72.6• | 71.9•/74.4• | 70.3•/71.2• | 71.0•/73.6• | 70.4•/75.2• | 73.8/78.5 |
| NCI Tumors | 63.4•/66.5• | 63.8•/69.6• | 65.7•/69.3• | 70.1•/72.8 | 71.8•/70.3• | 75.1•/72.3 | 72.1•/71.3 | 72.5•/73.8 | 73.6•/70.1• | 78.6/71.2 |
| Lung Cancer | 81.5•/85.6• | 80.8•/86.7• | 84.2•/88.5• | 87.9•/86.4• | 87.8•/90.9• | 91.5•/92.6 | 88.5•/89.3• | 90.6•/92.0 | 92.1•/91.5 | 94.7/92.2 |
| COAD | 60.8•/62.3• | 58.7•/61.3• | 59.1•/61.8• | 63.2•/64.9• | 72.4•/70.5 | 73.5/76.8 | 70.4•/71.1 | 71.8•/70.3 | 72.3•/68.4 | 74.6/69.1 |
| ENCA (subtype) | 59.4•/61.7• | 62.6•/67.3• | 64.6•/63.2• | 69.2•/71.8• | 72.6/73.9• | 70.5•/71.3• | 71.5•/69.6• | 72.0•/71.3• | 71.4•/69.5• | 73.6/75.9 |
| ENCA (stage) | 69.7•/71.8• | 70.3•/72.5• | 71.6•/74.3• | 70.5•/75.6• | 73.4•/75.8• | 78.2•/77.6• | 75.5•/76.3• | 75.2•/78.8• | 76.6•/79.1• | 81.5/83.8 |
| PRAD | 68.1•/69.2• | 68.8•/70.5• | 71.3•/75.1• | 73.6•/76.8• | 75.2•/77.3• | 75.8•/78.4• | 74.4•/73.6• | 76.0•/78.4• | 76.4•/80.2• | 80.6/82.9 |