Chasing intelligence in health data

Chasing intelligence in health data

Chasing intelligence in health data

Over the last few decades, the stream of data available to life sciences companies has grown from a trickle to a tidal wave: genetic and genomic portraits of individual patients, metabolomic and proteomic profiles, real-world data from wearables measuring everything from heart rate variability to blood glucose levels, detailed patient clinical histories from electronic health records.[1] The total volume of health data in the world is expected to soar to 2,314 exabytes by 2020, 15 times what it was in 2013. By some estimates, if this data were stored in a stack of tablet computers, the stack would reach 82,000 miles high.[2]

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Follow your heart to better recovery

Follow your heart to better recovery

Follow your heart to better recovery

Analyzing power files doesn’t make you faster. Training Stress Score (TSS) and Training Stress Balance (TSB) charts cannot say for certain whether you should go hard tomorrow or not. And a simple heart rate monitor won’t tell you when you are sick until it’s too late. But heart rate variability, or HRV for short — that’s a metric that could well be useful.

Follow your heart to better recovery

 

Will ‘Smart’ Solutions Really Transform Cardiology?

Will ‘Smart’ Solutions Really Transform Cardiology?

Will ‘Smart’ Solutions Really Transform Cardiology?

 

Smart technologies are often touted as the answer to some of cardiology’s greatest challenges in patient care and practice. But where does hyperbole end and reality begin with artificial intelligence, machine learning and deep learning? Even the most skeptical cardiologists can’t help but feel the digital waves lapping at […]