AIMC Topic: Lung Neoplasms
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Beam orientation optimization in IMRT using sparse mixed integer programming and non-convex fluence map optimization.
Physics in medicine and biology
Jul 4, 2025
Beam orientation optimization (BOO) in intensity-modulated radiation therapy (IMRT) is a complex, non-convex problem traditionally addressed with heuristic methods.This work demonstrates the potential improvement of the proposed BOO, providing a math...
Exploring the impact of neutrophils on lung adenocarcinoma using Mendelian randomization and transcriptomic study.
Scientific reports
Jul 3, 2025
Tumor immune microenvironment plays a crucial role in determining the prognosis of lung adenocarcinoma (LUAD), with the interaction of immune cells within this microenvironment contributing to a poorer prognosis. We sought to investigate the causal r...
Artificial intelligence-assisted endobronchial ultrasound for differentiating between benign and malignant thoracic lymph nodes: a meta-analysis.
BMC pulmonary medicine
Jul 2, 2025
BACKGROUND: Endobronchial ultrasound (EBUS) is a widely used imaging modality for evaluating thoracic lymph nodes (LNs), particularly in the staging of lung cancer. Artificial intelligence (AI)-assisted EBUS has emerged as a promising tool to enhance...
A deep learning-based computed tomography reading system for the diagnosis of lung cancer associated with cystic airspaces.
Scientific reports
Jul 2, 2025
To propose a deep learning model and explore its performance in the auxiliary diagnosis of lung cancer associated with cystic airspaces (LCCA) in computed tomography (CT) images. This study is a retrospective analysis that incorporated a total of 342...
Unveiling diagnostic biomarkers and therapeutic targets in lung adenocarcinoma using bioinformatics and experimental validation.
Scientific reports
Jul 2, 2025
Lung adenocarcinoma (LUAD) is a major challenge in oncology due to its complex molecular structure and generally poor prognosis. The aim of this study was to find diagnostic markers and therapeutic targets for LUAD by integrating differential gene ex...
Identification of exosome-related genes in NSCLC via integrated bioinformatics and machine learning analysis.
Scientific reports
Jul 2, 2025
Exosomes are crucial in the development of non-small cell lung cancer (NSCLC), yet exosome-associated genes in NSCLC remain insufficiently explored. The present study identified 59 exosome-associated differentially expressed genes (EA-DEGs) from the ...
AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis.
Scientific reports
Jul 2, 2025
Lung cancer remains the leading cause of cancer-related mortality worldwide, necessitating accurate and efficient diagnostic tools to improve patient outcomes. Lung segmentation plays a pivotal role in the diagnostic pipeline, directly impacting the ...
Developing an innovative lung cancer detection model for accurate diagnosis in AI healthcare systems.
Scientific reports
Jul 2, 2025
Accurate Lung cancer (LC) identification is a big medical problem in the AI-based healthcare systems. Various deep learning-based methods have been proposed for Lung cancer diagnosis. In this study, we proposed a Deep learning techniques-based integr...
Mapping the EORTC QLQ-C30 and QLQ-LC13 to the SF-6D utility index in patients with lung cancer using machine learning and traditional regression methods.
Health and quality of life outcomes
Jul 1, 2025
BACKGROUND: Preference-based measures of health-related quality of life (HRQoL), such as the Short Form Six-Dimension (SF-6D) is essential for health economic evaluations. However, these measures are rarely included in clinical trials for lung cancer...
Enhanced pulmonary nodule detection with U-Net, YOLOv8, and swin transformer.
BMC medical imaging
Jul 1, 2025
RATIONALE AND OBJECTIVES: Lung cancer remains the leading cause of cancer-related mortality worldwide, emphasizing the critical need for early pulmonary nodule detection to improve patient outcomes. Current methods encounter challenges in detecting s...
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