Deep learning-based computed tomography (CT) derived body composition classifier for colorectal cancer patients
Optimize deep learning models, particularly GoogLeNet and AlexNet, can automate CT-derived body composition analysis with a Mean Percentage Error of 4.96% for SMA and 8.12% for SMD, and have the potential to streamline clinical practice by reducing the time and expertise required for manual segmentation.