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MIT Technology Review

DeepMind’s algorithm can predict serious kidney injury 48 hours before it happens

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It’s only accurate a little more than half the time, though, raising questions over whether and how it could be used in real-life settings.

The news: DeepMind, Google’s artificial-intelligence unit, has created a deep-learning system that analyzes someone’s health records, including information such as vital signs and blood test results, and then predicts the chance of acute kidney injury (AKI). In a paper published in the journal Nature yesterday, researchers showed they were able to predict 55.8% of cases up to 48 hours before they occurred. For more severe kidney injuries, such as those that would require dialysis at a later stage, the accuracy was closer to 90%. 

The promise: AKI contributes to almost 300,000 deaths in the US every year, and affects one out of every five patients admitted to hospital in America for serious care. However, if it’s caught and treated early, it can be reversed. That’s why this system is so promising: it could potentially save a lot of lives.

However: It was built using records from the US Department of Veterans Affairs, a training data set that was 94% male. It would need a lot more testing to confirm its utility in the general population. There were also many false positives.

DeepMind plans to incorporate the algorithm into its Streams app, which helps doctors at London’s Royal Free Hospital to identify patients at risk of developing AKI. Only then, after further testing, can we say for sure just how useful it will be.

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