Rationale and Objectives to develop a deep learning radiomics graph network (DLRN) that
integrates deep learning features extracted from gray scale ultrasonography, radiomics …

Objectives To differentiate parotid pleomorphic adenoma (PA) from adenolymphoma (AL)
using radiomics of grayscale ultrasonography in combination with clinical features. Methods …

Background Pleomorphic adenoma (PA), often with the benign-like imaging appearances
similar to Warthin tumor (WT), however, is a potentially malignant tumor with a high …

Objective The pathological classification and imaging manifestation of parotid gland tumors
are complex, while accurate preoperative identification plays a crucial role in clinical …

Background The preoperative differentiation between benign parotid gland tumors (BPGTs)
and malignant parotid gland tumors (MPGTs) is of great significance for therapeutic decision …

Rationale and Objectives To develop, validate, and test a comprehensive radiomics
prediction model to distinguish parotid polymorphic adenomas (PAs) and warthin tumors …

Background Distinguishing parotid pleomorphic adenoma (PPA) from parotid
adenolymphoma (PA) is important for precision treatment, but there is a lack of readily …

Objective This study aims to investigate the value of machine learning models based on
clinical-radiological features and multiphasic CT radiomics features in the differentiation of …

Purpose To evaluate the effectiveness of MRI-based radiomics models in distinguishing
between Warthin tumors (WT) and misdiagnosed or ambiguous pleomorphic adenoma (PA) …

Objectives This study aimed to explore and validate the value of different radiomics models
for differentiating benign and malignant parotid tumors preoperatively. Methods This study …