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Artificial Intelligence-based Dietary Care System
Sponsor: National Taiwan University Hospital
Summary
Patients with rectal cancer complicated by low anterior resection syndrome who undergo anal-preserving surgery may experience severe distress in daily life due to changes in bowel function, thus requiring significant post-discharge care support from healthcare professionals. This study is a multicenter, non-blinded randomized controlled trial. One hundred patients with rectal cancer complicated by low anterior resection syndrome are planned to be randomly assigned in a 1:1 ratio from the colorectal surgery outpatient clinics of National Taiwan University Hospital, its Cancer Center, and its Yunlin Branch. They will be divided into a control group receiving routine dietary education and an experimental group receiving both routine dietary education and the use of an artificial intelligence-based dietary care system application. The artificial intelligence-based dietary care system application will be used for approximately six months. Three questionnaires will be administered at one month post-surgery (before intervention), three months post-surgery, and six months post-surgery. The questionnaires will include: a demographic data sheet, a low anterior resection syndrome score, distress inventory from altered bowel functioning, and the European Organization for Research and Treatment of Cancer QLQ-30 Scale, to verify the effectiveness of the artificial intelligence-based dietary care system application in improving bowel disturbance and quality of life in patients with rectal cancer complicated by low anterior resection syndrome.
Official title: Effectiveness of An Artificial Intelligence-based Dietary Care System for Distress From Altered Bowel Function and Quality of Life in Rectal Cancer Patients With Low Anterior Resection Syndrome
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
100
Start Date
2026-07-01
Completion Date
2028-12-31
Last Updated
2026-06-10
Healthy Volunteers
No
Conditions
Interventions
Artificial Intelligence-based Dietary Care System
1. Large language model-based communication for patient interaction, system guidance, analytic feedback, dietary recommendations, and referral information. 2. AI-driven image analysis using regional convolutional neural networks, linked to a database of over 100,000 meals and national dietary reference standards, enabling estimation of food types, portions, and nutrient intake. 3. Bowel movement tracking interface for recording time, frequency, and stool characteristics.
Routine Care
Content covers postoperative dietary progression, nutritional supplementation, intake principles, and food avoidance. The postoperative regimen typically advances through four stages-clear liquid, low-residue semi-liquid, low-residue soft, and regular diet-with most patients resuming normal intake within one month. Guidance emphasizes high-protein, high-calorie foods, small frequent meals, and balanced nutrition, while advising avoidance of gas-producing, odorous, coarse-fiber, greasy, spicy, pickled, and dairy products.
Locations (1)
National Taiwn University, College of Medicine
Taipei, Taiwan