Percival AI can uncover unseen health issues in CT scans
Researchers at the University of Pennsylvania have developed an AI model called Percival that can identify hidden health risks in routine CT scans. By analyzing vast amounts of historical patient data, the model can detect patterns that human radiologists might miss.
Why it matters
This technology represents a significant advancement in proactive, personalized healthcare by leveraging existing medical imaging for early disease detection.
by Perelman School of Medicine at the University of Pennsylvania
edited by Gaby Clark , reviewed by Robert Egan
This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:
Add to Preferred Sources Credit: Percival When analyzed by a new artificial intelligence model developed at Penn Medicine, CT scans reveal much about a patient's health beyond the specific condition they were originally ordered for, according to a new study published in npj Digital Medicine . The AI model, dubbed Percival, can uncover nearly hidden patterns in disease and potential future health risks that might have otherwise gone unnoticed by human eyes. While other models may need to be directed to find certain health conditions or outcomes, Percival can run in the background to pick up what is unseen.
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