DeepFAN, a transformer-based deep learning model for human-artificial intelligence collaborative assessment of incidental pulmonary nodules in CT scans: a multi-reader, multi-case trial

1. 1Train a transformer-based model on a large dataset of pathology-confirmed nodules
2. 2Integrate global and local features to improve classification accuracy
3. 3Conduct multi-reader, multi-case trials to validate the model's performance
4. 4Collaborate with human readers to assess and refine the model's output

Radiologists and AI engineers on a team benefit from DeepFAN as it improves the accuracy of nodule classification, while AI engineers can further develop and refine the model

💡 DeepFAN's transformer-based architecture effectively integrates global and local features for accurate nodule classification

💡 DeepFAN: AI-powered CT scan analysis for lung nodules