Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Künstliche Intelligenz in der Mammadiagnostik
1
Zitationen
3
Autoren
2025
Jahr
Abstract
CLINICAL/METHODICAL ISSUE: Artificial intelligence (AI) is being increasingly integrated into clinical practice. However, the specific benefits are still unclear to many users. STANDARD RADIOLOGICAL METHODS: In principle, AI applications are available for all imaging modalities, with a particular focus on mammography in breast diagnostics. METHODICAL INNOVATIONS: AI promises to filter examinations into negative and clearly positive findings, and thereby reduces part of the radiological workload. Other applications are not yet as widely established. PERFORMANCE: AI methods for mammography, and to a lesser extent tomosynthesis, have already reached the diagnostic quality of radiologists. ACHIEVEMENTS: Except for second-opinion applications/triage in mammography, most methods are still under development. PRACTICAL RECOMMENDATIONS: Currently, most AI applications must be critically evaluated by potential users regarding their maturity and practical benefits.
Ähnliche Arbeiten
A survey on deep learning in medical image analysis
2017 · 13.978 Zit.
pROC: an open-source package for R and S+ to analyze and compare ROC curves
2011 · 13.786 Zit.
Dermatologist-level classification of skin cancer with deep neural networks
2017 · 13.512 Zit.
A survey on Image Data Augmentation for Deep Learning
2019 · 12.117 Zit.
QuPath: Open source software for digital pathology image analysis
2017 · 8.417 Zit.