BACKGROUND AND OBJECTIVES: Hematologic toxicity (HT) is a common and serious side effect for advanced cervical cancer patients undergoing chemoradiotherapy. Accurately predicting HT can significantly improve patient management and treatment outcomes....
BACKGROUND: There is variability in overall survival among 2021 World Health Organization isocitrate dehydrogenase wild type glioblastoma (IDH-wt GBM) patients. The aim of the study was to develop a combined model for stratifying survival risk in IDH...
BACKGROUND: Patient satisfaction after one year of distal radius fracture fixation is influenced by various aspects such as the surgical approach, the patient's physical functioning, and psychological factors. Hence, a multimodal machine learning pre...
This study aimed to evaluate diffuse large B-cell lymphoma (DLBCL) patients who have refractory/relapsed disease and characterize the heterogeneity of DLBCL using patient-level radiomics analysis based on F-FDG PET/CT. A total of 132 patients diagnos...
Decisions regarding veno-venous extracorporeal membrane oxygenation (vv-ECMO) in patients with acute respiratory distress syndrome (ARDS) are often based solely on clinical and physiological parameters, which may insufficiently reflect severity and h...
PURPOSE: This study aimed to develop a Deep Learning Radiomics integrated model (DLRN), which combines photoacoustic/ultrasound(PA/US)imaging with clinical and radiomics features to distinguish between luminal and non-luminal BC in a preoperative set...
Journal of cancer research and clinical oncology
Sep 16, 2025
PURPOSE: Hepatocellular carcinoma (HCC) is a perilous malignant tumor, and transcatheter arterial chemoembolization (TACE) is a widely adopted treatment technique for advanced HCC. Nevertheless, TACE may not effectively reduce the risk of distant met...
In radiomics, feature selection methods are primarily used to eliminate redundant features and identify relevant ones. Feature projection methods, such as principal component analysis (PCA), are often avoided due to concerns that recombining features...
In radiomics, features are often linked to biomarkers and are generally expected to be reproducible, as reproducibility is considered a prerequisite for developing predictive models in clinical applications. However, this perspective overlooks featur...
Cancer imaging : the official publication of the International Cancer Imaging Society
Aug 29, 2025
BACKGROUND: This study aimed to develop a predictive model integrating multi-sequence MRI radiomics, deep learning features, and habitat imaging to forecast pathological complete response (pCR) in breast cancer patients undergoing neoadjuvant therapy...
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