AIMC Topic: Lung Neoplasms

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Efficiency of a computer-aided diagnosis (CAD) system with deep learning in detection of pulmonary nodules on 1-mm-thick images of computed tomography.

Japanese journal of radiology Jun 26, 2020
PURPOSE: To evaluate the performance of a deep learning-based computer-aided diagnosis (CAD) system at detecting pulmonary nodules on CT by comparing radiologists' readings with and without CAD.
Female Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Sensitivity and Specificity Male Humans Retrospective Studies Tomography, X-Ray Computed Middle Aged Lung Diagnosis, Computer-Assisted Deep Learning Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted
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Deep learning combined with radiomics may optimize the prediction in differentiating high-grade lung adenocarcinomas in ground glass opacity lesions on CT scans.

European journal of radiology Jun 25, 2020
PURPOSE: Adenocarcinoma (ADC) is the most common histological subtype of lung cancers in non-small cell lung cancer (NSCLC) in which ground glass opacifications (GGOs) found on computed tomography (CT) scans are the most common lesions. However, the ...
Adenocarcinoma of Lung Diagnosis, Differential Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Middle Aged Humans Lung Prognosis Deep Learning Lung Neoplasms Tomography, X-Ray Computed Female Reproducibility of Results Male
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Artificial intelligence-based collaborative filtering method with ensemble learning for personalized lung cancer medicine without genetic sequencing.

Pharmacological research Jun 23, 2020
In personalized medicine, many factors influence the choice of compounds. Hence, the selection of suitable medicine for patients with non-small-cell lung cancer (NSCLC) is expensive. To shorten the decision-making process for compounds, we propose a ...
Carcinoma, Non-Small-Cell Lung Cell Movement Apoptosis Cost-Benefit Analysis Antineoplastic Agents Humans Computer Simulation Cell Line, Tumor Artificial Intelligence Lung Neoplasms Precision Medicine Algorithms Clinical Decision-Making Databases, Factual Animals
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Perioperative outcomes of robot-assisted vs video-assisted and traditional open thoracic surgery for lung cancer: A systematic review and network meta-analysis.

The international journal of medical robotics + computer assisted surgery : MRCAS Jun 22, 2020
BACKGROUND: The superiority of robot-assisted thoracic surgery (RATS) over video-assisted thoracic surgery (VATS) and thoracotomy remains controversial for lung cancer.
Humans Robotics Pneumonectomy Thoracic Surgery, Video-Assisted Thoracic Surgery Retrospective Studies Network Meta-Analysis Length of Stay Lung Neoplasms
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Deep learning-based pulmonary nodule detection: Effect of slab thickness in maximum intensity projections at the nodule candidate detection stage.

Computer methods and programs in biomedicine Jun 20, 2020
BACKGROUND AND OBJECTIVE: To investigate the effect of the slab thickness in maximum intensity projections (MIPs) on the candidate detection performance of a deep learning-based computer-aided detection (DL-CAD) system for pulmonary nodule detection ...
Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Humans Sensitivity and Specificity Deep Learning Lung Neoplasms
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Deep Learning of Cancer Stem Cell Morphology Using Conditional Generative Adversarial Networks.

Biomolecules Jun 19, 2020
Deep-learning workflows of microscopic image analysis are sufficient for handling the contextual variations because they employ biological samples and have numerous tasks. The use of well-defined annotated images is important for the workflow. Cancer...
Mice, Inbred BALB C Optical Imaging Tumor Cells, Cultured Green Fluorescent Proteins Female Animals Deep Learning Image Processing, Computer-Assisted Lung Neoplasms Mice Neoplastic Stem Cells Mice, Nude
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Weakly-supervised learning for lung carcinoma classification using deep learning.

Scientific reports Jun 9, 2020
Lung cancer is one of the major causes of cancer-related deaths in many countries around the world, and its histopathological diagnosis is crucial for deciding on optimum treatment strategies. Recently, Artificial Intelligence (AI) deep learning mode...
Humans Neural Networks, Computer Artificial Intelligence Algorithms Supervised Machine Learning Diagnosis, Computer-Assisted Deep Learning Lung Neoplasms Computational Biology
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Identification of feature risk pathways of smoking-induced lung cancer based on SVM.

PloS one Jun 4, 2020
OBJECTIVE: The present study aims to explore the role of smoking factors in the risk of lung cancer and screen the feature risk pathways of smoking-induced lung cancer.
Databases, Genetic Cluster Analysis Area Under Curve ROC Curve High-Throughput Nucleotide Sequencing Smoking Humans Lung Neoplasms DNA, Neoplasm Risk Factors Signal Transduction Gene Ontology Gene Expression Profiling Support Vector Machine Protein Interaction Mapping
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Development and Validation of a Deep Learning Model for Non-Small Cell Lung Cancer Survival.

JAMA network open Jun 1, 2020
IMPORTANCE: There is a lack of studies exploring the performance of a deep learning survival neural network in non-small cell lung cancer (NSCLC).
Humans Prognosis Female Kaplan-Meier Estimate China Cohort Studies Survival Rate Aged Lung Neoplasms Aged, 80 and over Carcinoma, Non-Small-Cell Lung Male United States Young Adult Models, Statistical Middle Aged Adult Neoplasm Staging Deep Learning SEER Program
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Prognosis and Treatment of Non-Small Cell Lung Cancer in the Age of Deep Learning.

JAMA network open Jun 1, 2020
Lung Neoplasms Carcinoma, Non-Small-Cell Lung Neoplasm Staging Humans Prognosis Deep Learning
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