Development of a Precision Nutrition Expert System Combining AI Dietary Image Recognition and Big Data Analysis: A Case Study on Kidney Disease

NCT07829991 | Active Not Recruiting

• 1 other identifier: CMUH114-REC1-021
• Study Type: interventional
• Target: 50
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this interventional study is to evaluate a smartphone-based precision nutrition system for patients with chronic kidney disease (CKD). The main questions it aims to answer are:

1. 1.Do patients with CKD find the CKDCare system easy to use?
2. 2.Does using the system change patients' dietary intake, including the proportion of ultra-processed foods they consume?
3. 3.Use the CKDCare system in the LINE app for three months
4. 4.Take photos of their meals and record what they eat
5. 5.Complete a questionnaire about how easy the system is to use

Conditions

Chronic Kidney Disease

Keywords

Chronic Kidney Disease; Precision Nutrition; Artificial Intelligence; Chatbot; mHealth; Ultra-Processed Foods

Outcome Measures

Primary Outcomes (1)

• System Usability Scale (SUS) score

  Usability of the CKDCare system measured by the 10-item System Usability Scale. Total score ranges from 0 to 100, with higher scores indicating better perceived usability.

  At 3 months (end of the system trial period)

Secondary Outcomes (14)

• Estimated glomerular filtration rate (eGFR)

  Baseline and after the intervention (at 3 months)

• Blood urea nitrogen (BUN)

  Baseline and after the intervention (at 3 months)

• Serum creatinine

  Baseline and after the intervention (at 3 months)

• Serum albumin

  Baseline and after the intervention (at 3 months)

• Serum potassium

  Baseline and after the intervention (at 3 months)

Study Arms (1)

CKD patients

EXPERIMENTAL

Adults aged 20 years or older with a physician-diagnosed chronic kidney disease, recruited from the outpatient nutrition clinic. Participants used the CKDCare LINE chatbot to record their meals and receive personalized dietary advice for three months.

Device: CKDcare

Interventions

CKDcare DEVICE

Participants will use the CKDCare system, a dietitian-led LINE chatbot integrating dietary self-monitoring, personalized nutrition feedback, and nutrition education for CKD self-management.

CKD patients

Eligibility Criteria

• Age: 20 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• CKD patients:
• Aged 20 years or older
• Physician-diagnosed chronic kidney disease
• Available dietary records from the outpatient nutrition clinic
• Healthcare professionals:
• \- Clinical dietitian certified in CKD nutrition, CKD outpatient dietitian, or nephrologist

You may not qualify if:

• Younger than 20 years of age
• No available dietary records from the outpatient nutrition clinic

Sponsors & Collaborators

• China Medical University Hospital: lead

Study Sites (1)

China Medical University Hospital

Taichung, 40447, Taiwan

Location

MeSH Terms

Conditions

Renal Insufficiency, Chronic

Condition Hierarchy (Ancestors)

Renal Insufficiency; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: SUPPORTIVE CARE
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 13, 2026
• First Posted: September 21, 2026
• Study Start: March 25, 2026
• Primary Completion: September 30, 2026
• Study Completion: September 30, 2026
• Last Updated: September 21, 2026

Record last verified: 2026-09

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)