NCT06857344

Reinforcement Learned Automatic Anesthesia System During Painless Gastrointestinal Endoscopy

Automated Anesthesia System-Gastrointestinal Endoscopy (AAS-GE): a Reinforcement Learning Based Control for Anesthesia During Gastrointestinal Endoscopy

• Status: Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 164 (estimated)
• Sponsor: Boston Intelligent Medical Research Center, Shenzhen United Scheme Technology Co., Ltd. · Industry
• Sex: All
• Age: 18 Years – 65 Years
• Healthy volunteers: Accepted

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.

Conditions

• Anesthesia Induction

Interventions

Type	Name	Description
PROCEDURE	AI Controlled General Anesthesia	During gastrointestinal endoscopy, anesthesia will be induced using ciprofol, and controlled by an AI model.
PROCEDURE	General Anesthesia (GA)	Anesthesia will be induced using ciprofol, and controlled by experienced anesthesiologists.

Timeline

• Start date: 2025-05-01
• Primary completion: 2025-09-01
• Completion: 2025-10-01
• First posted: 2025-03-04
• Last updated: 2025-08-15

Locations

5 sites across 1 country: China