This comprehensive review unfolds a detailed narrative of Artificial Intelligence (AI) making
its foray into radiology, a move that is catalysing transformational shifts in the healthcare …

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 …

Recent technological advances in the field of artificial intelligence hold promise in
addressing medical challenges in breast cancer care, such as early diagnosis, cancer …

Background Radiomics has been applied for assessing lymphovascular invasion (LVI) in
patients with breast cancer. However, associations between features from peritumoral …

Background Breast cancer screening through mammography is crucial for early detection,
yet the demand for mammography services surpasses the capacity of radiologists. Artificial …

We performed a systematic review and a meta-analysis of studies using MRI-radiomics for
predicting the pathological complete response in breast cancer patients undergoing …

Simple Summary In this study, we trained and evaluated several machine-learning models
with the aim of predicting breast cancer lymph node metastasis in patients eligible for …

Simple Summary Breast cancer is one of the leading causes of cancer death among women.
Ultrasound is a harmless imaging modality used to help make decisions about who should …

Background In clinical practice, there are currently a variety of nomograms for predicting
lymph node metastasis (LNM) of prostate cancer. At the same time, some scholars have …

Breast cancer risk models represent the likelihood of developing breast cancer based on
risk factors. They enable personalized interventions to improve screening programs …