Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Performance of AI to exclude normal chest radiographs to reduce radiologists’ workload
12
Zitationen
9
Autoren
2024
Jahr
Abstract
The AI system reached an AUC of 0.92 for the detection of normal chest radiographs. Fifty-three percent of normal chest radiographs were identified with a NPV of 98% for urgent findings. AI can reduce the workload of chest radiography reporting by 15%.
Ähnliche Arbeiten
Refinement and reassessment of the SERVQUAL scale.
1991 · 3.966 Zit.
Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review
2005 · 3.755 Zit.
Radiobiology for the Radiologist.
1974 · 3.501 Zit.
International evidence-based recommendations for point-of-care lung ultrasound
2012 · 2.807 Zit.
Radiation Dose Associated With Common Computed Tomography Examinations and the Associated Lifetime Attributable Risk of Cancer
2009 · 2.427 Zit.