Machine learning technique may detect age-related muscle wasting

Scientists have developed a novel machine learning technique that predicts the biological age of a muscle and may help combat sarcopenia, the degenerative loss of skeletal muscle and its function. Age-associated muscle wasting remains an important clinical challenge that impacts hundreds of millions of older adults. It is associated with serious negative health outcomes such as falls, impaired standing balance, physical disability, and mortality. Researchers from US-based artificial intelligence company, Insilico Medicine, developed a novel deep-learning based model that predicts the biological age of a muscle and can be used to estimate the relevant importance of the genetic and epigenetic factors driving this process within many age groups. The research, published in the journal Frontiers in Genetics, explains one of the simple models for applying the age predictors developed using several machine learning techniques.