FIGURE 5.

Representative of visualized COVID‐19 and CAP cases using gradient‐weighted class activation mapping (Grad‐CAM) on the small dataset trained model in the independent external test set. (a) (1∼2), original axial computed tomography (CT) images of COVID‐19 and CAP cases; (b) (1∼2) and (c) (1∼2), attention heat maps generated using Grad‐CAM for three dimensional convolutional neural network (3D CNN) and MIL‐LSTM in the discrimination between COVID‐19 and CAP; (d) (1∼2), reference annotation by senior radiologists. 3DMTM detected more inflammation lesions than 3DCM and shared a good consistency with the gold standardization annotated by senior radiologists. CAP, community‐acquired pneumonia; COVID‐19, coronavirus disease 2019; Grad‐CAM, gradient‐weighted class activation mapping; MIL‐LSTM, multi‐instance learning with the long and short‐term memory; 3D CNN, 3 dimensional convolutional neural network; 3DMTM, 3D‐MIL‐LSTM algorithm; 3DCM, 3D CNN model