RATIONALE AND OBJECTIVES: This study aims to analyze the intratumoral and peritumoral characteristics of lung adenocarcinoma patients on the basis of chest CT images via radiomic and deep learning methods and to develop and validate a multimodel fusi...
Lung cancer remains one of the leading causes of cancer-related deaths worldwide, with early detection being critical to improving patient outcomes. Recent advancements in deep learning have shown promise in enhancing diagnostic accuracy, particularl...
Lung cancer has been stated as one of the prevalent killers of cancer up to this present time and this clearly underlines the rationale for early diagnosis to enhance life expectancy of patients afflicted with the condition. The reasons behind the us...
BACKGROUND: Patients with early-stage non-small cell lung cancer (NSCLC) typically receive surgery as their primary form of treatment. However, studies have shown that a high proportion of these patients will experience a recurrence after their resec...
RATIONALE AND OBJECTIVES: To explore the feasibility of deep learning (DL)-enhanced, fully automated bone mineral density (BMD) measurement using the ultralow-voltage 80 kV chest CT scans performed for lung cancer screening.
The British journal of general practice : the journal of the Royal College of General Practitioners
May 2, 2025
BACKGROUND: The journey of >80% of patients diagnosed with lung cancer starts in general practice. About 75% of patients are diagnosed when it is at an advanced stage (3 or 4), leading to >80% mortality within 1 year at present. The long-term data in...
BACKGROUND: Epidermal growth factor receptor (EGFR) mutations are present in 10-60% of all non-small cell lung cancer (NSCLC) patients and are associated with dismal prognosis. Lung cancer brain metastases (LCBM) are a common complication of lung can...
PURPOSE: This study was designed to construct progressive binary classification models based on radiomics and deep learning to predict the presence of epidermal growth factor receptor ( EGFR ) and TP53 mutations and to assess the models' capacities t...
PURPOSE: To evaluate the accuracy of ultra-low dose (ULD) chest computed tomography (CT), with a radiation exposure equivalent to a 2-view chest x-ray, for pulmonary nodule detection using deep learning image reconstruction (DLIR).
BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patients with epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma. However, not all patients with EGFR mutations respond to TKIs. This study...
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