German CheXpert Chest X-ray Radiology Report Labeler
This addresses the problem of efficient annotation for chest X-ray classification in German radiology, though it is incremental as it adapts an existing method to a new language.
The study developed an algorithm to automatically extract annotations from German chest X-ray reports, reducing manual labeling time and improving modeling performance, with the model trained on these labels performing competitively against manually labeled data and strongly outperforming models on public data.
This study aimed to develop an algorithm to automatically extract annotations for chest X-ray classification models from German thoracic radiology reports. An automatic label extraction model was designed based on the CheXpert architecture, and a web-based annotation interface was created for iterative improvements. Results showed that automated label extraction can reduce time spent on manual labeling and improve overall modeling performance. The model trained on automatically extracted labels performed competitively to manually labeled data and strongly outperformed the model trained on publicly available data.