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Muscle-Specific Multimodal AI for Sarcopenia Diagnosis

NCT07477574 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 75

Last updated 2026-03-17

No results posted yet for this study

Summary

This study aims to develop a muscle-specific multimodal artificial intelligence (AI) model for the diagnosis of sarcopenia and to investigate the effects of rehabilitation training on muscle aging. Clinical, functional, and imaging data will be collected from participants with muscle function decline. Multimodal data, including muscle function measurements and clinical assessments, will be integrated to develop and validate an AI-based diagnostic model for sarcopenia. In addition, the effects of rehabilitation training on muscle function and muscle aging-related outcomes will be evaluated. The results of this study are expected to contribute to the development of digital biomarkers and precision rehabilitation strategies for sarcopenia.

Conditions

Interventions

BEHAVIORAL

Rehabilitation training

Participants will perform a structured rehabilitation training program designed to improve muscle strength, physical performance, and muscle function. Clinical assessments and muscle function measurements will be collected before and after the rehabilitation program to evaluate the effects of training and to support the development of a muscle-specific multimodal AI model for sarcopenia diagnosis.

Sponsors & Collaborators

  • Seoul National University Bundang Hospital

    lead OTHER

Study Design

Allocation
NA
Purpose
BASIC_SCIENCE
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
65 Years
Max Age
85 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-03-01
Primary Completion
2028-02-28
Completion
2028-02-28

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Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07477574 on ClinicalTrials.gov