AIMC Topic: Solitary Pulmonary Nodule

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A teacherless lightweight classification framework for benign and malignant pulmonary nodules based on GAS.

Biomedical physics & engineering express
Deep learning methods have been widely adopted for classifying benign and malignant pulmonary nodules. However, existing models often suffer from high memory usage, computational cost, and large parameter counts. As a result, the development of light...

Flexible state space modelling for accurate and efficient 3D lung nodule detection.

Biomedical physics & engineering express
Early and accurate detection of pulmonary nodules in computed tomography (CT) scans is critical for reducing lung cancer mortality. While convolutional neural networks (CNNs) and Transformer-based architectures have been widely used for this task, th...

Precise diagnosis of small invasive pulmonary nodules driven by single-cell immune signatures in peripheral blood.

Nature communications
Early detection of lung cancer is crucial for improving patient outcomes. However, accurately diagnosing invasive pulmonary nodules and predicting tumor invasiveness remain major clinical challenges. Given the established role of immune dysfunction i...

Hybrid radiomic-HOG ensemble model for accurate pulmonary nodule diagnosis.

Biomedical physics & engineering express
Lung cancer remains one of the deadliest forms of cancer worldwide, making early and accurate pulmonary-nodule classification essential for improving patient prognosis. This study presents a robust ensemble-stacking framework that integrates Histogra...

Predictive radiomicsĀ based ensemble machine learning approach in CT lung nodule diagnosis.

Journal of the Egyptian National Cancer Institute
BACKGROUND: Computed tomography imaging, a non-invasive tool, is used around the globe by medical professionals to identify and diagnose lung cancer; a lethal disease with high rates of occurrence and mortality globally. Radiomics extracted from medi...

Machine learning and discriminant analysis model for predicting benign and malignant pulmonary nodules.

BMC medical informatics and decision making
BACKGROUND: Pulmonary Nodules (PNs) are a trend considered as the early manifestation of lung cancer. Among them, PNs that remain stable for more than two years or whose pathological results suggest not being lung cancer are considered benign PNs (BP...

Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography.

BMC pulmonary medicine
BACKGROUND: Pulmonary nodules seen by computed tomography (CT) can be benign or malignant, and early detection is important for optimal management. The existing manual methods of identifying nodules have limitations, such as being time-consuming and ...

Enhanced pulmonary nodule detection with U-Net, YOLOv8, and swin transformer.

BMC medical imaging
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...

Radiomic 'Stress Test': exploration of a deep learning radiomic model in a high-risk prospective lung nodule cohort.

BMJ open respiratory research
BACKGROUND: Indeterminate pulmonary nodules (IPNs) are commonly biopsied to ascertain a diagnosis of lung cancer, but many are ultimately benign. The Lung Cancer Prediction (LCP) score is a commercially available deep learning radiomic model with str...

[Incidental pulmonary nodules on CT imaging: what to do?].

Nederlands tijdschrift voor geneeskunde
Incidental pulmonary nodules are very frequently found on CT imaging and may represent (early stage) lung cancers without any signs or symptoms. These incidental findings can be solid lesions or ground glass lesions that may be solitary or multiple. ...