Table 7 Performances of machine learning-based methods
From: Discovering and identifying New York heart association classification from electronic health records
NYHA Classification | Precision | Recall | F-Measure |
|---|---|---|---|
Feature Set 1: bag-of-words | |||
Support Vector Machine | |||
I | 84.71% | 82.06% | 83.36% |
II | 88.30% | 91.80% | 90.01% |
III | 88.34% | 88.46% | 88.40% |
IV | 80.00% | 70.81% | 75.13% |
Overall | 85.34% | 83.28% | 84.23% |
Logistic Regression | |||
I | 83.61% | 79.97% | 81.75% |
II | 86.87% | 91.99% | 89.36% |
III | 87.66% | 88.46% | 88.06% |
IV | 80.72% | 64.11% | 71.47% |
Overall | 84.72% | 81.13% | 82.66% |
Random Forest | |||
I | 87.54% | 86.93% | 87.24% |
II | 91.23% | 94.40% | 92.79% |
III | 91.83% | 90.40% | 91.11% |
IV | 79.89% | 72.25% | 75.88% |
Overall | 87.63% | 86.00% | 86.75% |
Feature Set 2: n-gram | |||
Support Vector Machine | |||
I | 95.05% | 93.73% | 94.39% |
II | 95.71% | 96.81% | 96.26% |
III | 94.95% | 95.20% | 95.08% |
IV | 89.66% | 87.08% | 88.35% |
Overall | 93.84% | 93.21% | 93.52% |
Logistic Regression | |||
I | 93.09% | 91.46% | 92.27% |
II | 94.74% | 95.66% | 95.20% |
III | 93.12% | 94.81% | 93.96% |
IV | 87.18% | 81.34% | 84.16% |
Overall | 90.03% | 90.82% | 90.42% |
Random Forest | |||
I | 97.02% | 96.52% | 96.77% |
II | 97.58% | 97.49% | 97.54% |
III | 93.01% | 96.63% | 94.78% |
IV | 93.99% | 82.30% | 87.76% |
Overall | 95.40% | 92.23% | 93.78% |