New artificial intelligence-based tools can help clinicians predict which hospitalized patients face a high risk of developing acute kidney injury (AKI).

TOP INSIGHT
Acute kidney injury is common among hospitalized patients and has a significant impact on morbidity and mortality.
The Dascena algorithm outperformed SOFA, demonstrating superior performance in predicting acute kidney injury 72 hours prior to onset.
"Through earlier detection, physicians can proactively treat their patients, potentially resulting in better outcomes and limiting the severity of AKI symptoms," said Ritankar Das, MSc, president, and chief executive officer of Dascena. "This presentation highlights our algorithm's ability to provide this earlier detection over traditional systems, which could profoundly impact AKI management in the hospital setting in the future."
Dascena has received Breakthrough Device Designation from the U.S. Food and Drug Administration for its AKI algorithm. This is the first Breakthrough Device Designation of a machine learning algorithm developed for the early detection of AKI.
Study: "Development and Validation of a Convolutional Neural Network Model for ICU Acute Kidney Injury Prediction"
Source-Eurekalert
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