Nat MedJClub
Large-scale esophageal cancer screening through noncontrast computed tomography and artificial intelligence.
Nature Medicine · · Multicenter Study · Open access
Zhou, Guo + more
Abstract ↗AI summary
The abstract is read at the publisher; the summary is JClub's.
EAGLE AI model detects early esophageal cancer with 90% sensitivity and 98.5% specificity from chest CT scans across multiple centers, enabling scalable screening.
- Why it matters: Early detection of esophageal cancer remains challenging due to the lack of accurate, noninvasive, and scalable screening tools, risking delayed diagnosis and treatment.
- What they did: The study trained and validated the EAGLE AI model on over 80,000 patients from diverse international cohorts using chest noncontrast CT scans, assessing its performance in real-world screening settings.
- The result: EAGLE achieved high accuracy in identifying precancerous and early-stage cancers, reducing false positives significantly and demonstrating potential to improve early detection and screening efficiency globally.
The findingWhy it mattersWhat they didThe result
- Open access