OBJECTIVES: Body composition assessment using CT images at the L3-level is increasingly applied in cancer research and has been shown to be strongly associated with long-term survival. Robust high-throughput automated segmentation is key to assess la...
OBJECTIVE: We aimed to develop and validate a deep learning system for fully automated segmentation of abdominal muscle and fat areas on computed tomography (CT) images.
Obesity is a low-grade chronic inflammatory state, in which a cytokine chemerin with its immunometabolic modulation has an important role. We aimed to study in a healthy population relationships between serum chemerin levels, lifestyle choices and ma...
IMPORTANCE: Increased ability to quantify anatomical phenotypes across multiple organs provides the opportunity to assess their cumulative ability to identify individuals at greatest susceptibility for adverse outcomes.
BACKGROUND: The adoption of robotic systems for gastric cancer surgery has been proven feasible and safe; however, a benefit over the laparoscopic approach has not yet been well-documented. We aimed to investigate the surgical outcomes of robotic ver...
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