BACKGROUND: Knowledge-based planning (KBP) is a data-driven approach that utilizes the knowledge from previous high-quality treatment plans to predict dose-volume histogram (DVH) parameters for organs-at-risk (OARs) in new cases. Research has demonst...
OBJECTIVE: This study aims to develop and validate a PET/CT radiomics fusion model for preoperative predicting pleural invasion (PI) in non-small cell lung cancer (NSCLC) patients.
RATIONALE AND OBJECTIVES: Radiogenomics holds promise in identifying molecular alterations in nonsmall cell lung cancer (NSCLC) using imaging features. Previously, we developed a radiogenomics model to predict epidermal growth factor receptor (EGFR) ...
Nonsmall cell lung cancer (NSCLC) is a lethal cancer and lacks robust biomarkers for noninvasive clinical diagnosis. Detecting NSCLC at the early stage can decrease the mortality rate and minimise harm caused by various treatments. We curated 2050 sa...
PURPOSE: This study aims to develop and validate a multiregional radiomics model to predict pathological complete response (pCR) to neoadjuvant chemoimmunotherapy in non-small cell lung cancer (NSCLC), and further evaluate the performance of the mode...
PURPOSE: This study was designed to evaluate the postoperative frailty status of patients with non-small cell lung cancer, identify influencing factors, establish a machine learning-based prediction model, and explore the correlation between frailty ...
Biochemical and biophysical research communications
Jul 22, 2025
The direction of anticancer therapies has changed in recent years, including the increasing use of immunotherapy. However, around 50 % of non-small-cell lung cancer (NSCLC) patients do not respond to immunotherapy. Therefore, it is important to find ...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 1, 2025
Accurate segmentation of lung tumors is essential for advancing personalized medicine in non-small cell lung cancer (NSCLC). However, stage IV NSCLC presents significant challenges due to heterogeneous tumor morphology and the presence of associated ...
OBJECTIVE: Interest has grown in combining radiology, pathology, genomic, and clinical data to improve the accuracy of diagnostic and prognostic predictions toward precision health. However, most existing works choose their datasets and modeling appr...
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