Background and purpose In comparison to conventional medical imaging diagnostic
modalities, the aim of this overview article is to analyze the accuracy of the application of …

Objectives We systematically reviewed the current literature evaluating the ability of fully-
automated deep learning (DL) and semi-automated traditional machine learning (TML) MRI …

Background Clinically significant prostate cancer (PCa) diagnosis at MRI requires accurate
and efficient radiologic interpretation. Although artificial intelligence may assist in this task …

Abstract Objectives To assess Prostate Imaging Reporting and Data System (PI-RADS)–
trained deep learning (DL) algorithm performance and to investigate the effect of data size …

Purpose Radiomic features are promising quantitative parameters that can be extracted from
medical images and employed to build machine learning predictive models. However …

Prostate cancer (PCa) is the most frequent male malignancy and the assessment of PCa
aggressiveness, for which a biopsy is required, is fundamental for patient management …

Purpose To systematically review and evaluate the methodological quality of studies using
radiomics for diagnostic and predictive purposes in patients with intracranial meningioma …

The high incidence of rectal cancer in both sexes makes it one of the most common tumors,
with significant morbidity and mortality rates. To define the best treatment option and …

Artificial intelligence developments are essential to the successful deployment of community-
wide, MRI-driven prostate cancer diagnosis. AI systems should ensure that the main benefits …