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AI technology can predict your age by gathering physical activity data from smartphones and wearables- Technology News, Firstpost

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Artificial Intelligence (AI) technology can produce improved digital biomarkers of ageing and frailty via gathering physical activity data from smartphones and other wearables, a new study suggests. According to the researchers from the longevity biotech company GERO and Moscow Institute of Physics and Technology (MIPT), AI is a powerful tool in pattern recognition and has demonstrated outstanding performance in visual object identification, speech recognition and other fields. "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 co-author Peter Fedichev, Science Director at GERO. "Inspired by these examples, we explored AI potential for'Health Risks Assessment' based on human physical activity," Fedichev added. For the study, published in the journal Scientific Reports, researchers analysed physical activity records and clinical data from a large 2003-2006 US National Health and Nutrition Examination Survey (NHANES). They trained neural network to predict biological age and mortality risk of the participants from one-week long stream of activity measurements.


Hacking the aging code: Big data to the rescue

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Aging is the most important single factor behind chronic diseases and death. As «silver tsunami» approaches, healthcare and social protection systems face the looming crisis. By 2050, the global population of older persons is projected to more than double its size in 2015. New article published in Frontiers in Genetics by MIPT scientist Peter Fedichev describes a strategy for systematic development of novel anti-aging therapeutics and biomarkers of aging using the data from medical studies and large biobanks. The mortality rate in humans increases exponentially with age and doubles approximately every eight years.


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

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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).


Artificial Intelligence Can Predict Your Age - Republic World

#artificialintelligence

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).


Hacking the aging code: Big data for saving human lives

#artificialintelligence

Aging is the most important single factor behind chronic diseases and death. As «silver tsunami» approaches, healthcare, and social protection systems face the looming crisis. By 2050, the global population of older persons is projected to more than double its size in 2015. The new article published in Frontiers in Genetics by MIPT scientist Dr. P. Fedichev describes a strategy for the systematic development of novel anti-aging therapeutics and biomarkers of aging using the data from medical studies and large biobanks. The mortality rate in humans increases exponentially with age and doubles approximately every eight years.