DeepMind's AI predicts kidney injury up to 48 hours before it happens TMG Pulse

Acute kidney injury, or AKI, is a condition in which the kidneys stop filtering waste products from the blood. It occurs quickly (in two days or less) and debilitates an estimated 1 in 5 hospitalized patients in the U.K. and 1 in 4 hospitalized patients in the U.S. Worse still, because it's difficult to detect, AKI kills upwards of 600,000 people annually in both countries combined despite the more than $1.2 billion (£1 billion) the U.K.'s National Health Service (NHS) spends treating it each year. The U.K.-based AI research firm said it's made progress toward automated systems addressing the 11% of failures to detect AKI deterioration in U.S. hospitals and the 30% of preventable cases globally. Over the course of two separate joint studies conducted with the U.S. Department of Veterans Affairs and The Royal Free London NHS Foundation Trust (RFL), DeepMind's health care division -- DeepMind Health -- investigated ways to flag AKI warning signs clinicians might otherwise fail to spot. The resulting pair of papers published in the Journal of Medical Internet Research (JMIR) and Nature Digital Medicine reveal the fruit of the organizations' labor: an algorithm that can predict the presence of AKI up to 48 hours in advance and an app that cuts missed AKI cases from 12.4% to 3.3%.