Artificial Inteligence in Endoscopic Ultrasound
- Conditions
- Pancreas DiseasePancreatic CancerPancreatic Cyst
- Interventions
- Device: Patients undergoing endoscopic ultrasound procedures
- Registration Number
- NCT06564571
- Lead Sponsor
- Orlando Health, Inc.
- Brief Summary
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.
- Detailed Description
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.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 1500
- Age ≥ 18 years
- Any patient undergoing endoscopic ultrasound examination
- Age < 18 years
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Patients undergoing endoscopic ultrasound procedures Patients undergoing endoscopic ultrasound procedures Patients will undergo endoscopic ultrasound procedures as planned. Abnormalities in the pancreas identified by the endoscopist during the endoscopic ultrasound examination will be correlated against those detected by the AI platform.
- Primary Outcome Measures
Name Time Method Rate of detection pancreatic abnormalities by AI 1 day Ability of AI to detect pancreatic abnormalities as identified by an endoscopist during EUS examination of the pancreas.
- Secondary Outcome Measures
Name Time Method Rate of detection pancreatic solid mass lesions by AI 1 day Ability of AI to detect pancreatic solid mass lesions as identified by an endoscopist during EUS examination of the pancreas.
Rate of detection pancreatic cystic lesions by AI 1 day Ability of AI to detect pancreatic cystic lesions as identified by an endoscopist during EUS examination of the pancreas.
Trial Locations
- Locations (1)
Orlando Health
🇺🇸Orlando, Florida, United States