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To build the model, the team used data collected from 374 adults 19 to 82 years of age. The data included participant demographics, such as age, BMI, blood pressure and physical activity levels ...

With this proof-of-concept, we integrated RWD into predictive modeling using ML techniques to predict clinical outcomes and explore their potential implications for clinical decision making. The ...

Recently, ML has emerged as a viable method to harness large volumes of health care data and predict disease risk across a broad swath of clinical domains. 16 - 19 Yet, to our knowledge, to date, ...

By Ayo Onikoyi In a landmark contribution to petroleum engineering, Nigerian researcher Prosper Nekekpemi has developed a machine learning model that significantly improves the prediction of ...

Metabolite data and AI combine to redefine how we measure aging and predict health spans. Study: Metabolomic age (MileAge) predicts health and life span: A comparison of multiple machine learning ...