How Artificial intelligence can predict biological age based on smartphone, wearables data

Artificial intelligence (AI) can produce digital biomarkers of ageing and frailty by gathering physical activity data from smartphones and other wearables, scientists have found. The finding, published in the journal Scientific Reports, untaps the emerging potential of combining wearable sensors and AI technologies for continuous health risk monitoring with real-time feedback to life and health insurance, healthcare and wellness providers. "Artificial Intelligence is a powerful tool in pattern recognition and has demonstrated outstanding performance in visual object identification, speech recognition, and other fields," said Peter Fedichev from the Moscow Institute of Physics and Technology (MIPT) in Russia. "Recent promising examples in the field of medicine include neural networks showing cardiologist-level performance in detection of arrhythmia in ECG data, deriving biomarkers of age from clinical blood biochemistry, and predicting mortality based on electronic medical records," said Fedichev. The researches analysed physical activity records and clinical data from a large 2003-2006 US National Health and Nutrition Examination Survey (NHANES).