Muscle-Specific Multimodal AI for Sarcopenia Diagnosis (SARC-AI)
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About
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.
Enrollment
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Inclusion criteria
- Adults aged 65 years or older
- Individuals with reduced muscle function or at risk of sarcopenia
- Able to participate in rehabilitation training
- Able to understand the study procedures and provide written informed consent
Exclusion criteria
- Severe cardiovascular, neurological, or musculoskeletal conditions that limit participation in exercise
- Severe cognitive impairment
- Participation in other clinical trials that may influence study outcomes
- Any medical condition judged by the investigator to make participation unsafe
Trial design
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Interventional model
Masking
75 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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