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Multimodal AI-Assisted Bowel Preparation for Colonoscopy
Sponsor: Chiayi Christian Hospital
Summary
This randomized controlled trial aims to evaluate the effectiveness of a multimodal artificial intelligence (AI)-assisted smartphone application in improving bowel preparation outcomes among hospitalized adults undergoing colonoscopy. A total of 140 participants will be randomly assigned in a 1:1 ratio to either an experimental group or a control group. The control group will receive conventional written and verbal nursing education, while the experimental group will receive the same standard education plus a multimodal AI-assisted application delivered through the LINE platform. The application provides structured bowel preparation education, interactive AI-based question-and-answer support, dietary image recognition, stool image analysis, and individualized feedback. Study outcomes will include bowel preparation knowledge, satisfaction with nursing education, and bowel cleansing quality assessed using the Aronchick Scale.
Official title: Exploring the Effectiveness of a Multimodal Artificial Intelligence Application on Bowel Preparation Outcomes for Colonoscopy
Key Details
Gender
All
Age Range
20 Years - Any
Study Type
INTERVENTIONAL
Enrollment
140
Start Date
2026-03-10
Completion Date
2027-01-31
Last Updated
2026-09-10
Healthy Volunteers
No
Conditions
Interventions
Multimodal AI-Assisted Bowel Preparation Education
Participants in the experimental group receive conventional bowel preparation education plus a multimodal AI-assisted application delivered through the LINE platform. The application provides structured education on bowel preparation, dietary restrictions, bowel cleansing medication, and examination procedures; interactive AI-based question-and-answer support; dietary image recognition; stool image analysis; and individualized feedback throughout the bowel preparation process. Food images are analyzed to classify dietary patterns as clear liquid, low-residue, or regular diet, while stool images are analyzed using multimodal AI and a convolutional neural network model to assess bowel cleansing status and provide feedback.
Locations (1)
Chiayi Christian Hospital
Chiayi City, Taiwan, Taiwan