Deep learning (DL) has the potential to transform medical diagnostics. However, the
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …

This review gives an overview of the current state of deep learning research in breast cancer
imaging. Breast imaging plays a major role in detecting breast cancer at an earlier stage, as …

This paper aims to provide a review of the basis for application of AI in radiology, to discuss
the immediate ethical and professional impact in radiology, and to consider possible future …

Multiparametric magnetic resonance imaging (mpMRI) has been shown to improve
radiologists' performance in the clinical diagnosis of breast cancer. This machine learning …

Multimodal medical imaging plays a pivotal role in clinical diagnosis and research, as it
combines information from various imaging modalities to provide a more comprehensive …

Machine learning is increasingly integrated into clinical practice, with applications ranging
from pre-clinical data processing, bedside diagnosis assistance, patient stratification …

Screening for breast cancer reduces breast cancer–related mortality and earlier detection
facilitates less aggressive treatment. Unfortunately, current screening modalities are …

Breast magnetic resonance imaging (MRI) is the most sensitive imaging modality for breast
cancer diagnosis and is widely used clinically. Dynamic contrast-enhanced MRI is the basis …

Medical imaging techniques, such as mammography, ultrasound and magnetic resonance
imaging, plays an integral role in the detection and characterization of breast cancer …

DWI is a noncontrast MRI technique that measures the diffusion of water molecules within
biologic tissue. DWI is increasingly incorporated into routine breast MRI examinations …