BACKGROUND: The potential prognostic value of extranodal soft tissue metastasis (ESTM) has been confirmed by increasing studies about gastric cancer (GC). However, the gold standard of ESTM is determined by pathologic examination after surgery, and t...
OBJECTIVES: To investigate the model-, code-, and data-sharing practices in the current radiomics research landscape and to introduce a radiomics research database.
PURPOSE: This study aims to develop and validate a deep learning radiomics nomogram (DLRN) for prediction of axillary lymph node metastasis (ALNM) in breast cancer patients.
Journal of magnetic resonance imaging : JMRI
Aug 9, 2023
BACKGROUND: Cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) homozygous deletion has been verified as an independent and critical biomarker of negative prognosis and short survival in isocitrate dehydrogenase (IDH)-mutant astrocytoma. Therefore, non...
RATIONALE AND OBJECTIVES: Accurately assessing epidermal growth factor receptor (EGFR) mutation status in head and neck squamous cell carcinoma (HNSCC) patients is crucial for prognosis and treatment selection. This study aimed to construct and valid...
This study aimed to develop a machine learning model for predicting brain arteriovenous malformation (bAVM) rupture using a combination of traditional risk factors and radiomics features. This multicenter retrospective study enrolled 586 patients wit...
Journal of magnetic resonance imaging : JMRI
May 24, 2023
BACKGROUND: Diagnostic performance of placenta accreta spectrum (PAS) by prenatal MRI is unsatisfactory. Deep learning radiomics (DLR) has the potential to quantify the MRI features of PAS.
Biomedical physics & engineering express
Mar 23, 2023
To determine glioma grading by applying radiomic analysis or deep convolutional neural networks (DCNN) and to benchmark both approaches on broader validation sets.Seven public datasets were considered: (1) low-grade glioma or high-grade glioma (369 p...