AIMC Topic: Solitary Pulmonary Nodule

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

BMC medical informatics and decision making Jul 18, 2025
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...
Machine Learning Female Aged Adult Humans Multiple Pulmonary Nodules Solitary Pulmonary Nodule Diagnosis, Differential Discriminant Analysis Male Middle Aged Case-Control Studies Lung Neoplasms
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Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography.

BMC pulmonary medicine Jul 12, 2025
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 ...
Neural Networks, Computer Multiple Pulmonary Nodules Artificial Intelligence Solitary Pulmonary Nodule Algorithms Humans Sensitivity and Specificity Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Deep Learning Lung Neoplasms Support Vector Machine
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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...
Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Humans Algorithms Tomography, X-Ray Computed Deep Learning
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Radiomic 'Stress Test': exploration of a deep learning radiomic model in a high-risk prospective lung nodule cohort.

BMJ open respiratory research Jun 27, 2025
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...
Multiple Pulmonary Nodules Solitary Pulmonary Nodule Biopsy Aged Radiomics Male Middle Aged Risk Assessment Deep Learning ROC Curve Lung Neoplasms Prospective Studies Retrospective Studies Tomography, X-Ray Computed Female Humans
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[Incidental pulmonary nodules on CT imaging: what to do?].

Nederlands tijdschrift voor geneeskunde Jun 23, 2025
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. ...
Multiple Pulmonary Nodules Solitary Pulmonary Nodule Incidental Findings Humans Tomography, X-Ray Computed Male Female Middle Aged Aged Lung Neoplasms Adenocarcinoma
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Development and interpretation of machine learning-based prognostic models for predicting high-risk prognostic pathological components in pulmonary nodules: integrating clinical features, serum tumor marker and imaging features.

Journal of cancer research and clinical oncology Jun 17, 2025
BACKGROUND: With the improvement of imaging, the screening rate of Pulmonary nodules (PNs) has further increased, but their identification of High-Risk Prognostic Pathological Components (HRPPC) is still a major challenge. In this study, we aimed to ...
Humans Machine Learning Prognosis Retrospective Studies Tomography, X-Ray Computed Female Middle Aged Aged Lung Neoplasms Adult Multiple Pulmonary Nodules Biomarkers, Tumor Solitary Pulmonary Nodule Male
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Detection of Pulmonary Nodules on Ultra-low Dose Chest Computed Tomography With Deep-learning Image Reconstruction Algorithm.

Journal of thoracic imaging May 1, 2025
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).
Radiation Dosage Humans Radiography, Thoracic Algorithms Aged, 80 and over Adult Lung Neoplasms Sensitivity and Specificity Multiple Pulmonary Nodules Cross-Sectional Studies Prospective Studies Solitary Pulmonary Nodule Male Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Middle Aged Female Lung Aged Deep Learning
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A comparison of an integrated and image-only deep learning model for predicting the disappearance of indeterminate pulmonary nodules.

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...
Retrospective Studies Tomography, X-Ray Computed Female Aged Humans Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Male Middle Aged Deep Learning
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Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks.

BMC cancer Apr 10, 2025
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 ...
Male Female Humans Pneumonectomy Middle Aged Preoperative Period Neural Networks, Computer Aged Lung Neoplasms Retrospective Studies Preoperative Care Adult Solitary Pulmonary Nodule Tomography, X-Ray Computed Radiomics
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Lung nodule detection using a multi-scale convolutional neural network and global channel spatial attention mechanisms.

Scientific reports Apr 10, 2025
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,...
Solitary Pulmonary Nodule False Positive Reactions Algorithms Tomography, X-Ray Computed Convolutional Neural Networks Lung Neoplasms Humans
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