AIMC Topic: Lung Neoplasms

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Identifying invasiveness to aid lung adenocarcinoma diagnosis using deep learning and pathomics.

Scientific reports Feb 10, 2025
Most classification efforts for primary subtypes of lung adenocarcinoma (LUAD) have not yet been integrated into clinical practice. This study explores the feasibility of combining deep learning and pathomics to identify tumor invasiveness in LUAD pa...
Female Aged Male Humans Retrospective Studies Lung Neoplasms Neoplasm Invasiveness Area Under Curve Middle Aged Deep Learning ROC Curve Adenocarcinoma of Lung
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A Novel Deep Learning-Based (3D U-Net Model) Automated Pulmonary Nodule Detection Tool for CT Imaging.

Current oncology (Toronto, Ont.) Feb 8, 2025
BACKGROUND: Precise detection and characterization of pulmonary nodules on computed tomography (CT) is crucial for early diagnosis and management.
Solitary Pulmonary Nodule Algorithms Tomography, X-Ray Computed Female Deep Learning Lung Neoplasms Multiple Pulmonary Nodules Humans
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Adaptive genetic algorithm based deep feature selector for cancer detection in lung histopathological images.

Scientific reports Feb 8, 2025
Cancer is a global health concern because of a significant mortality rate and a wide range of affected organs. Early detection and accurate classification of cancer types are crucial for effective treatment. Imaging tests on different image modalitie...
Image Processing, Computer-Assisted Algorithms Humans Lung Neoplasms Lung Genetic Algorithms Neural Networks, Computer Deep Learning
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Explainable Classification of Benign-Malignant Pulmonary Nodules With Neural Networks and Information Bottleneck.

IEEE transactions on neural networks and learning systems Feb 6, 2025
Computerized tomography (CT) is a clinically primary technique to differentiate benign-malignant pulmonary nodules for lung cancer diagnosis. Early classification of pulmonary nodules is essential to slow down the degenerative process and reduce mort...
Solitary Pulmonary Nodule Humans Neural Networks, Computer Algorithms Databases, Factual Tomography, X-Ray Computed Lung Neoplasms
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Cross-ViT based benign and malignant classification of pulmonary nodules.

PloS one Feb 5, 2025
The benign and malignant discrimination of pulmonary nodules plays a very important role in diagnosing the extent of lung cancer lesions. There are many methods using Convolutional neural network (CNN) for benign and malignant classification of pulmo...
Humans Multiple Pulmonary Nodules Neural Networks, Computer Solitary Pulmonary Nodule Algorithms Lung Neoplasms
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Automated recognition and segmentation of lung cancer cytological images based on deep learning.

PloS one Jan 31, 2025
Compared with histological examination of lung cancer, cytology is less invasive and provides better preservation of complete morphology and detail. However, traditional cytological diagnosis requires an experienced pathologist to evaluate all sectio...
Cytodiagnosis Bronchoalveolar Lavage Fluid ROC Curve Image Processing, Computer-Assisted Lung Neoplasms Algorithms Deep Learning Humans Neural Networks, Computer
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Tumor Cellularity Assessment Using Artificial Intelligence Trained on Immunohistochemistry-Restained Slides Improves Selection of Lung Adenocarcinoma Samples for Molecular Testing.

The American journal of pathology Jan 30, 2025
Tumor cellularity (TC) in lung adenocarcinoma slides submitted for molecular testing is important in identifying actionable mutations, but lack of best practice guidelines results in high interobserver variability in TC assessments. An artificial int...
Observer Variation Immunohistochemistry Adenocarcinoma of Lung Artificial Intelligence Reproducibility of Results Lung Neoplasms Humans
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The use of artificial intelligence to aid the diagnosis of lung cancer - A retrospective-cohort study.

Radiography (London, England : 1995) Jan 30, 2025
INTRODUCTION: AI software in the form of deep learning-based automatic detection (DLAD) algorithms for chest X-ray (CXR) interpretation have shown success in early detection of lung cancer (LC), however, there remains uncertainty related to clinical ...
Humans Artificial Intelligence Algorithms Retrospective Studies Tomography, X-Ray Computed Female Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Male Aged Deep Learning Aged, 80 and over Lung Neoplasms Sensitivity and Specificity
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Deep Learning-Assisted Computer-Aided Diagnosis System for Early Detection of Lung Cancer.

Journal of clinical ultrasound : JCU Jan 29, 2025
PURPOSE: The largest cause of cancer-related fatalities worldwide is lung cancer. The dimensions and positioning of the primary tumor, the presence of lesions, the type of lung cancer like malignant or benign, and the good mental health diagnosis all...
Humans Neural Networks, Computer Diagnosis, Computer-Assisted Algorithms Deep Learning Sensitivity and Specificity Lung Lung Neoplasms Early Detection of Cancer
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A machine learning-based 18F-FDG PET/CT multi-modality fusion radiomics model to predict Mediastinal-Hilar lymph node metastasis in NSCLC: a multi-centre study.

Clinical radiology Jan 29, 2025
AIM: To develop and validate a machine learning (ML) model based on positron emission tomography/computed tomography (PET/CT) multi-modality fusion radiomics to improve the prediction efficiency of mediastinal-hilar lymph node metastasis (LNM).
Fluorodeoxyglucose F18 Mediastinum Radiomics Lymphatic Metastasis Male Lung Neoplasms Positron Emission Tomography Computed Tomography Female Humans Middle Aged Lymph Nodes Machine Learning Radiopharmaceuticals Aged Carcinoma, Non-Small-Cell Lung Retrospective Studies Adult
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