Lung cancer remains the leading cause of cancer-related mortality worldwide, with its early detection and effective treatment posing significant clinical challenges. Radiomics, the extraction of quantitative features from medical imaging, has emerged...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 11, 2025
BACKGROUND: Indeterminate pulmonary nodules (IPNs) require follow-up CT to assess potential growth; however, benign nodules may disappear. Accurately predicting whether IPNs will resolve is a challenge for radiologists. Therefore, we aim to utilize d...
The expression levels of microRNAs (miRNAs) are strongly linked to cancer progression, making them promising biomarkers for cancer detection. Enzyme-free signal amplification DNA circuits have facilitated the detection of low-abundance miRNAs. Howeve...
Radiomics refers to the utilization of automated or semi-automated techniques to extract and analyze numerous quantitative features from medical images, such as computerized tomography (CT) or magnetic resonance imaging (MRI) scans. This study aims t...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 10, 2025
Computed tomography (CT)-derived ventilation estimation, also known as CT ventilation imaging (CTVI), is emerging as a potentially crucial tool for designing functional avoidance radiotherapy treatment plans and evaluating therapy responses. However,...
OBJECTIVE: The infiltration status of pulmonary ground-glass nodules (GGNs) exhibits significant variability, demanding tailored surgical strategies and individualized postoperative adjuvant therapies. This study explored the preoperative assessment ...
Early detection of lung nodules is crucial for the prevention and treatment of lung cancer. However, current methods face challenges such as missing small nodules, variations in nodule size, and high false positive rates. To address these challenges,...
Drug response prediction (DRP) is a central task in the era of precision medicine. Over the past decade, the emergence of deep learning (DL) has greatly contributed to addressing DRP challenges. Notably, the prediction of DRP for cancer cell lines be...
Epidermal growth factor receptor (EGFR) is a potential target for anticancer therapies and plays a crucial role in cell growth, survival, and metastasis. EGFR gene mutations trigger aberrant signaling, leading to non-small cell lung cancer (NSCLC). T...
. The dose distribution of lung cancer patients treated with the CyberKnife (CK) system is influenced by various factors, including tumor location and the direction of CK beams. The objective of this study is to present a deep learning approach that ...
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