Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Diagnostic capabilities of artificial intelligence as an additional reader in a breast cancer screening program
24
Zitationen
8
Autoren
2024
Jahr
Abstract
• Incorporating AI as a triage tool in screening workflow improves sensitivity (72.38%) and specificity (92.86%), enhancing detection rates for interval and missed cancers. • AI-assisted triaging is effective in differentiating low and high-risk cases, reduces radiologist workload, and potentially enables broader screening coverage. • AI has the potential to facilitate early diagnosis compared to human reading.
Ähnliche Arbeiten
A survey on deep learning in medical image analysis
2017 · 13.514 Zit.
Dermatologist-level classification of skin cancer with deep neural networks
2017 · 13.137 Zit.
A survey on Image Data Augmentation for Deep Learning
2019 · 11.743 Zit.
QuPath: Open source software for digital pathology image analysis
2017 · 8.113 Zit.
Radiomics: Images Are More than Pictures, They Are Data
2015 · 7.988 Zit.