Simple Summary The integration of artificial intelligence (AI) into radiomic models has
become increasingly popular due to advances in computer-aided diagnosis tools. These …

Purpose Radiomics in uro-oncology is a rapidly evolving science proving to be a novel
approach for optimizing the analysis of massive data from medical images to provide …

Background The purpose of this study is to investigate the use of radiomics and deep
features obtained from multiparametric magnetic resonance imaging (mpMRI) for grading …

Objective To develop and validate a multimodal MRI-based radiomics nomogram for
predicting clinically significant prostate cancer (CS-PCa). Methods Patients who underwent …

目的基于前列腺影像报告和数据系统2.1 版(Prostate Imaging Reporting and Data System
version 2.1, PI-RADS v2. 1) 分析双参数磁共振成像(biparametric magnetic resonance …

Radiomics integrated with artificial intelligence offers a pioneering approach to urologic
oncology, ushering in an era of enhanced diagnostic precision and reduced invasiveness …

Background: Prostate Cancer (PCa) is asymptomatic at an early stage and often painless,
requiring only active surveillance. External Beam Radiotherapy (EBRT) is currently a …

Objective To test the ability of high-performance machine learning (ML) models employing
clinical, radiological, and radiomic variables to improve non-invasive prediction of the …

Introduction Gliomas are still considered as challenging in oncologic management despite
the developments in treatment approaches. The complete elimination of a glioma might not …

Objective To compare the performance of different imaging classifiers in the prospective
diagnosis of prostate diseases based on multiparameter MRI. Methods A total of 238 …