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Demonstrates the ability to predict muscle mass in older adults, suggesting a cost-effective screening tool for sarcopenia.
This study highlights the potential of machine learning for predicting skeletal muscle mass using non-invasive anthropometric measurements. These findings support the proposed model as a scalable and cost-effective tool for estimating skeletal muscle mass, which is a key quantitative component of sarcopenia screening.
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Jun‐hee Kim (2026) studied this question.
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