AIMC Topic: Solitary Pulmonary Nodule

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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...
Biopsy Retrospective Studies Tomography, X-Ray Computed Female ROC Curve Humans Aged Lung Neoplasms Prospective Studies Multiple Pulmonary Nodules Middle Aged Radiomics Risk Assessment Solitary Pulmonary Nodule Male Deep Learning
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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. ...
Humans Tomography, X-Ray Computed Female Aged Male Solitary Pulmonary Nodule Middle Aged Incidental Findings Lung Neoplasms Adenocarcinoma Multiple Pulmonary Nodules
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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 ...
Aged Adult Biomarkers, Tumor Male Prognosis Retrospective Studies Tomography, X-Ray Computed Female Middle Aged Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Humans Machine Learning
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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).
Deep Learning Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiography, Thoracic Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Cross-Sectional Studies Male Prospective Studies Middle Aged Tomography, X-Ray Computed Lung Female Aged Humans Aged, 80 and over Algorithms Adult Sensitivity and Specificity
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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...
Humans Retrospective Studies Tomography, X-Ray Computed Female Deep Learning Aged Lung Neoplasms Multiple Pulmonary Nodules Sensitivity and Specificity Solitary Pulmonary Nodule Male Radiographic Image Interpretation, Computer-Assisted Middle Aged
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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 ...
Neural Networks, Computer Retrospective Studies Tomography, X-Ray Computed Preoperative Care Female Humans Lung Neoplasms Radiomics Solitary Pulmonary Nodule Male Aged Pneumonectomy Middle Aged Adult Preoperative Period
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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,...
Convolutional Neural Networks Lung Neoplasms Humans Solitary Pulmonary Nodule Algorithms False Positive Reactions Tomography, X-Ray Computed
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Exploring non-invasive biomarkers for pulmonary nodule detection based on salivary microbiomics and machine learning algorithms.

Scientific reports Mar 29, 2025
Microorganisms are one of the most promising biomarkers for cancer, and the relationship between microorganisms and lung cancer occurrence and development provides significant potential for pulmonary nodule (PN) diagnosis from a microbiological persp...
Male Female Middle Aged Bayes Theorem Humans Aged RNA, Ribosomal, 16S Saliva Case-Control Studies Machine Learning Solitary Pulmonary Nodule Adult Microbiota Lung Neoplasms Algorithms Biomarkers, Tumor Biomarkers
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Leveraging Artificial Intelligence as a Safety Net for Incidentally Identified Lung Nodules at a Tertiary Center.

Journal of the American College of Surgeons Mar 17, 2025
BACKGROUND: Artificial intelligence (AI)-powered platforms may be used to ensure that clinically significant lung nodules receive appropriate management. We studied the impact of a commercially available AI natural language processing tool on the det...
Tertiary Care Centers Incidental Findings Safety-net Providers Lung Neoplasms Multiple Pulmonary Nodules Electronic Health Records Solitary Pulmonary Nodule Female Natural Language Processing Aged Male Middle Aged Humans Artificial Intelligence Retrospective Studies Tomography, X-Ray Computed
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OMS-CNN: Optimized Multi-Scale CNN for Lung Nodule Detection Based on Faster R-CNN.

IEEE journal of biomedical and health informatics Mar 6, 2025
The global increase in lung cancer cases, often marked by pulmonary nodules, underscores the critical importance of timely detection to mitigate cancer progression and reduce morbidity and mortality. The Faster R-CNN approach is a two-stage, high-pre...
Lung Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Algorithms Tomography, X-Ray Computed
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