This site is not optimized for Internet Explorer 8 (or older).
Please upgrade to a newer version of Internet Explorer or use an alternate browser such as Chrome or Firefox.
Using Artificial Intelligence to Predict Future Acute Kidney Injury
Using deep learning employing data from over 700,000 patients (6 billion data points), an algorithm for continuous prediction of the risk of acute kidney injury (AKI) was developed. The model correctly predicted over 90% of AKI requiring dialysis with a lead time of up to 48 hours, with 2 false alerts for every true alert.