Three-dimensional body composition parameters using automatic volumetric segmentation allow accurate prediction of colorectal cancer outcomes.

Aiya BimurzayevaMin Jung KimJong-Sung AhnGa Yoon KuDokyoon MoonJinsun ChoiHyo Jun KimHan-Ki LimRumi ShinJi Won ParkSeung-Bum RyooKyu Joo ParkHan-Jae ChungJong-Min KimSang Joon ParkSeung-Yong Jeong

Published in: Journal of cachexia, sarcopenia and muscle (2023)

3D volumetric parameters generated using an automatic segmentation program showed higher correlations with the short- and long-term outcomes of patients with CRC than conventional 2D parameters.

Keyphrases

body composition
deep learning
convolutional neural network
resistance training
bone mineral density
machine learning
quality improvement
metabolic syndrome
adipose tissue
postmenopausal women
high intensity
weight loss