Volumetric visceral fat machine learning phenotype on CT for differential diagnosis of inflammatory bowel disease.
Ziling ZhouZiman XiongRan ChengQingyu LuoYuanqiu LiQingguo XiePeng XiaoDaoyu HuXuemei HuYaqi ShenZhen LiPublished in: European radiology (2022)
• High-output feature data extracted from volumetric visceral adipose tissue on CT enterography had an effective diagnostic performance for differentiating Crohn's disease from ulcerative colitis. • With adjustment of clinical covariates that cause difference in volumetric visceral adipose tissue, adjusted clinical machine learning model reached stronger performance when distinguishing Crohn's disease patients from ulcerative colitis patients.
Keyphrases
- adipose tissue
- machine learning
- ulcerative colitis
- insulin resistance
- end stage renal disease
- newly diagnosed
- ejection fraction
- prognostic factors
- computed tomography
- peritoneal dialysis
- big data
- deep learning
- contrast enhanced
- high fat diet
- metabolic syndrome
- skeletal muscle
- patient reported outcomes
- patient reported
- pet ct