Deep learning-based chest CT analysis is efficient for COVID-19 diagnosis, but large labeled datasets are scarce. We propose ResNext+, a weakly-supervised approach using volume-level labels, lung segmentation, spatial features, LSTM, and slice attention for slice-level predictions.It shows an 81.9% precision and 81.4% F1 score, which can be further enhanced with image enhancement techniques.

• COVID-19 Diagnosis
• Deep Learning
• Medical Imaging