Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...
Abstract: Patient-reported outcomes (PROs), directly captured from cancer patients undergoing radiation therapy, play a crucial role in guiding clinicians’ counseling on treatment-related toxicities.
Abstract: Quantum machine learning (QML) presents a promising avenue for addressing complex classification challenges, yet its application in medical imaging remains largely unexplored. This work ...
Background: 3D medical image segmentation is a cornerstone for quantitative analysis and clinical decision-making in various modalities. However, acquiring high-quality voxel-level annotations is both ...
Elon Musk’s X has become a top site for images of people that have been non-consensually undressed by AI, according to a third-party analysis, with thousands of instances each hour over a day earlier ...
Objective To evaluate the prevalence and anatomical distribution of inflammatory and structural MRI lesions in axial spondyloarthritis (axSpA) and compare these between patients with isolated axial ...