Deep learning using computed tomography to identify high-risk patients for acute small bowel obstructio
- Conditions
- Diseases of the digestive system
- Registration Number
- KCT0008330
- Lead Sponsor
- Ajou University
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Completed
- Sex
- All
- Target Recruitment
- 600
The inclusion criteria were: (1) Older than 18 years, (2) CT image findings with SBO, (3) Mechanism of obstruction caused by the adhesion. Before this process, we identified normal subjects (n = 1000) without any abnormal abdominal CT findings during the health screenings conducted in 2019.
Patients under the age of 18, intestinal obstruction caused by inflammatory bowel disease, intestinal obstruction caused by cancer, intestinal obstruction caused by cancer, intestinal disintegration caused by duodenum or colon obstruction, and intestinal obstruction within two weeks of abdominal surgery. In addition to the above findings, clinical cases that are not considered to be intestinal obstruction due to small intestine obstruction are excluded.
Study & Design
- Study Type
- Observational Study
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method AUROC
- Secondary Outcome Measures
Name Time Method sensitivity, specificity, accuracy