Artificial Intelligence in Endoscopic Ultrasound
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 310
- 试验地点
- 1
- 主要终点
- Rate of detection pancreatic abnormalities by AI
研究概览
简要总结
The objective of the study is to determine if this artificial intelligence system is capable of detecting abnormalities in the pancreas that are identified by an endoscopist at endoscopic ultrasound procedures.
详细描述
Endoscopic Ultrasound (EUS) is an equipment where an ultrasound transducer is attached to the tip of the endoscope. When advanced to the stomach the organs outside such as the pancreas and liver can be visualized in great detail. This enables diagnosis of conditions such as pancreatic cancer. However, an endoscopist must undergo training to accurately interpret these ultrasound images.
The investigators are in the process of developing an artificial intelligence system that could potentially interpret EUS images. The objective of the study is to determine if this artificial intelligence system is capable of detecting abnormalities in the pancreas that are identified by an endoscopist at endoscopic ultrasound procedures. Such correlation if established will lead to possible development of an artificial intelligence platform that can diagnose pancreatic diseases. Such development will potentially minimize human error and decrease learning curve to gain proficiency in EUS.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 100 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age ≥ 18 years
- •Any patient undergoing endoscopic ultrasound examination
排除标准
- •Age < 18 years
结局指标
主要结局
Rate of detection pancreatic abnormalities by AI
时间窗: 1 day
Ability of AI to detect pancreatic abnormalities as identified by an endoscopist during EUS examination of the pancreas.
次要结局
- Rate of detection pancreatic solid mass lesions by AI(1 day)
- Rate of detection pancreatic cystic lesions by AI(1 day)