Abstract Purpose of Review For uterine cervical cancer, the recently revised International
Federation of Gynecology and Obstetrics (FIGO) staging system (2018) incorporates …

Radiomics is an emerging field of research that aims to find associations between
quantitative information extracted from imaging examinations and clinical data to support the …

Objective To explore an MRI-based radiomics nomogram for preoperatively predicting of
pelvic lymph node (PLN) metastasis in patients with early-stage cervical cancer (ECC) …

Background Parkinson's disease (PD) is an irreversible neurodegenerative disease. The
diagnosis of PD based on neuroimaging is usually with low-level or deep learning features …

Objective: To develop and validate a radiomics predictive model based on multiparameter
MR imaging features and clinical features to predict lymph node metastasis (LNM) in …

Purpose To develop and identify a MRI-based radiomics nomogram for the preoperative
prediction of parametrial invasion (PMI) in patients with early-stage cervical cancer (ECC) …

Objective To investigate the feasibility of a noninvasive detection of lymph node metastasis
(LNM) for early-stage cervical cancer (ECC) patients with radiomics methods based on the …

Cervical cancer is the most commonly diagnosed cancer among women. Early diagnosis
and prediction will greatly improve the treatment outcome. Many clinical parameters have …

Background To investigate the magnetic resonance imaging (MRI)-based radiomics value in
predicting the survival of patients with locally advanced cervical squamous cell cancer …

This prospective study explored the application of texture features extracted from T2WI and
apparent diffusion coefficient (ADC) maps in predicting recurrence of advanced cervical …