Table 5. The measurements of the method that used the TextCNN model only and the method that used our MSCNN for the 12 disease categories.
| Disease | Precision | Recall | F1-score | |||||
|---|---|---|---|---|---|---|---|---|
| TextCNN | MSCNN | TextCNN | MSCNN | TextCNN | MSCNN | |||
| AURI | 0.56 | 0.75 | 0.59 | 0.77 | 0.58 | 0.76 | ||
| Bronchitis | 0.49 | 0.68 | 0.68 | 0.82 | 0.55 | 0.74 | ||
| Asthma | 0.48 | 0.68 | 0.26 | 0.45 | 0.32 | 0.5 | ||
| Pharyngitis | 0.41 | 0.58 | 0.25 | 0.42 | 0.29 | 0.48 | ||
| Pneumonia | 0.46 | 0.65 | 0.23 | 0.45 | 0.26 | 0.53 | ||
| Rhinitis | 0.37 | 0.58 | 0.23 | 0.43 | 0.33 | 0.49 | ||
| Tonsillitis | 0.27 | 0.45 | 0.11 | 0.29 | 0.17 | 0.35 | ||
| Laryngitis | 0.50 | 0.68 | 0.38 | 0.57 | 0.38 | 0.6 | ||
| Nasosinusitis | 0.49 | 0.68 | 0.28 | 0.45 | 0.34 | 0.51 | ||
| FLU | 0.19 | 0.36 | 0.05 | 0.19 | 0.07 | 0.26 | ||
| FBAO | 0.53 | 0.72 | 0.16 | 0.33 | 0.27 | 0.4 | ||
| Others | 0.39 | 0.56 | 0.22 | 0.48 | 0.30 | 0.48 | ||
Metrics included precision, recall, and F1-score. TextCNN, text convolutional neural network; MSCNN, medical-semantic-aware convolution neural network; AURI, acute upper respiratory infection; FLU, influenza; FBAO, foreign body airway obstruction.