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Reinforcement Learned Automatic Anesthesia System During Painless Gastrointestinal Endoscopy
Sponsor: Boston Intelligent Medical Research Center, Shenzhen United Scheme Technology Co., Ltd.
Summary
The goal of this clinical trial is to compare the performance difference between trained model and clinical professionals in anesthesia control during gastrointestinal endoscopy. The participants would include adults aged between 18-65 years old with ASA scores I-II. The main questions it aims to answer are: * Can AI model successfully and safely perform anesthesia during gastrointestinal endoscopy? * Researchers hypothesis that anesthesia performed by professionals is not inferior to those performed by AI model. The researchers will compare the results of the AI group with the traditional group to see if both groups have similar success rates in performing anesthesia. Participants will fast for 8 hours before the procedure, and drinking water will be prohibited for 2 hours after taking the intestinal purgatives.
Official title: Automated Anesthesia System-Gastrointestinal Endoscopy (AAS-GE): a Reinforcement Learning Based Control for Anesthesia During Gastrointestinal Endoscopy
Key Details
Gender
All
Age Range
18 Years - 65 Years
Study Type
INTERVENTIONAL
Enrollment
164
Start Date
2025-05-01
Completion Date
2025-10-01
Last Updated
2025-08-15
Healthy Volunteers
Yes
Conditions
Interventions
AI Controlled General Anesthesia
During gastrointestinal endoscopy, anesthesia will be induced using ciprofol, and controlled by an AI model.
General Anesthesia (GA)
Anesthesia will be induced using ciprofol, and controlled by experienced anesthesiologists.
Locations (5)
Anxi County Hospital
Anxi, Fujian, China
Jinjiang Municipal Hospital, Shanghai Sixth People's Hospital Fujian Campus
Jinjiang, Fujian, China
Xinzheng Public People's Hospital
Xinzheng, Henan, China
Henan Provincial People's Hospital
Zhengzhou, Henan, China
Zhengzhou Central Hospital
Zhengzhou, Henan, China