Study Using Deep Learning-based Artificial Intelligence for the Diagnosis of Small Bowel Obstruction
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 入组人数
- 17
- 试验地点
- 1
- 主要终点
- The diagnosis of the obstruction site
研究概览
简要总结
The study will compare the diagnostic accuracy and time to diagnosis of computed tomography images of patients with suspected intestinal obstruction seen in the emergency room by residents and surgeons, with and without artificial intelligence.
详细描述
DESIGN: This is an diagnostic study. SETTING: We developed a deep learning-based AI technology to automatically extract the intestinal tract from CT images using 5 200 CT images of 158 patients. The CT images of patients who visited the emergency department and were suspected of small bowel obstruction between June 6 and July 26, 2018, were obtained from two tertiary referral centers, which were used as the test samples. Data analysis was completed in December 2023.
PARTICIPANTS: Residents and surgeons participated in the study. INTERVENTIONS: Residents and surgeons were divided into two groups: one group read using the AI technology, and the other group read without the AI technology.
MAIN OUTCOMES AND MEASURES: Participants indicated whether or not small bowel obstruction and obstruction location. The time for diagnosis was also collected. We applied a hierarchical Bayesian model.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Other
入排标准
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Persons with documented consent
排除标准
- •Persons without documented consent
结局指标
主要结局
The diagnosis of the obstruction site
时间窗: September, 2024
Accuracy of diagnosis of the obstruction site
次要结局
未报告次要终点
研究者
Aitaro Takimoto
Medical Staff
Nagoya University