表 2. Comparison results between the method in this paper and the single-task classification method.
本文方法与单任务分类方法的对比结果
算法 | ACC | AUC | REC | PPV | NPV | F1 |
He等[18] | 78.44% ± 3.36% | 79.49% ± 4.73% | 66.19% ± 14.75% | 69.90% ± 3.73% | 77.19% ± 4.16% | 63.45% ± 8.32% |
Huang等[19] | 79.11% ± 4.23% | 77.25% ± 4.51% | 63.84% ± 8.15% | 64.50% ± 7.10% | 73.01% ± 5.96% | 59.80% ± 8.04% |
Carreira等[20] | 78.89% ± 1.92% | 81.06% ± 3.86% | 71.05% ± 12.41% | 68.79% ± 9.31% | 81.10% ± 3.13% | 65.34% ± 8.02% |
Zhou等[9] | 78.22% ± 1.68% | 79.25% ± 1.43% | 67.67% ± 3.95% | 68.32% ± 6.35% | 77.86% ± 2.90% | 63.30% ± 3.70% |
Yang等[3] | 80.67% ± 1.15% | 80.47% ± 1.06% | 60.89% ± 3.30% | 68.50% ± 6.73% | 78.24% ± 2.01% | 61.22% ± 2.23% |
本文算法 | 80.67% ± 0.67% | 79.09% ± 3.16% | 86.08% ± 0.83% | 80.07% ± 1.95% | 62.67% ± 2.54% | 80.05% ± 1.70% |