Publications by authors named "Zi-Chen An"
Article Synopsis
- The study evaluates a deep learning model's ability to classify clear cell renal cell carcinoma (ccRCC) into low-grade and high-grade using contrast-enhanced ultrasound (CEUS) images.
- A total of 6412 CEUS images from 177 patients were analyzed, with the model achieving notable performance metrics including sensitivity of 74.8%, specificity of 79.1%, and an AUC of 0.852.
- The results indicate that the deep learning model offers an effective non-invasive method for differentiating ccRCC grades, potentially aiding in clinical decisions.
