Machine Learning Based Prediction: Health Behavior on BP

ML algorithm + individual data = personalized recommendations to reduce blood pressure


Source: UC San Diego Jacobs School of Engineering, Po-Han Chiang and Sujit Dey, Mobile Systems Design Lab, Dept. of Electrical and Computer Engineering

Using wearable off-the-shelf technology and machine learning, UC San Diego researchers have developed a method to predict an individual’s blood pressure and provide personalized recommendations to lower it based on this data.

The researchers believe this is the first work investigating daily blood pressure prediction and its relationship to health behavior data collected by wearables.

Read more:
Technical paper is here
UCSD summary is here

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