AIMC Topic: Lung

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Validation of a Deep Learning Algorithm for the Detection of Malignant Pulmonary Nodules in Chest Radiographs.

JAMA network open Sep 1, 2020
IMPORTANCE: The improvement of pulmonary nodule detection, which is a challenging task when using chest radiographs, may help to elevate the role of chest radiographs for the diagnosis of lung cancer.
Aged Sensitivity and Specificity Male Middle Aged Lung Artificial Intelligence Algorithms Female Reproducibility of Results Predictive Value of Tests Radiologists Tumor Burden Radiography, Thoracic Radiographic Image Enhancement Humans Deep Learning Lung Neoplasms Solitary Pulmonary Nodule Early Detection of Cancer
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Detection of pulmonary nodules based on a multiscale feature 3D U-Net convolutional neural network of transfer learning.

PloS one Aug 26, 2020
A new computer-aided detection scheme is proposed, the 3D U-Net convolutional neural network, based on multiscale features of transfer learning to automatically detect pulmonary nodules from the thoracic region containing background and noise. The te...
Solitary Pulmonary Nodule Humans Early Detection of Cancer Tomography, X-Ray Computed Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted Lung Machine Learning Imaging, Three-Dimensional Algorithms Lung Neoplasms
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Development and Validation of a Modified Three-Dimensional U-Net Deep-Learning Model for Automated Detection of Lung Nodules on Chest CT Images From the Lung Image Database Consortium and Japanese Datasets.

Academic radiology Aug 21, 2020
RATIONALE AND OBJECTIVES: A more accurate lung nodule detection algorithm is needed. We developed a modified three-dimensional (3D) U-net deep-learning model for the automated detection of lung nodules on chest CT images. The purpose of this study wa...
Humans Retrospective Studies Tomography, X-Ray Computed Lung Deep Learning Lung Neoplasms Japan
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Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets.

Nature communications Aug 14, 2020
Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of CT scans for differentiation of COVID-19 findings from other ...
Coronavirus Infections COVID-19 Testing Clinical Laboratory Techniques Betacoronavirus Pneumonia, Viral Child, Preschool Child Imaging, Three-Dimensional Radiographic Image Interpretation, Computer-Assisted Aged Aged, 80 and over Young Adult Adult Male Algorithms Middle Aged Tomography, X-Ray Computed Lung Female Deep Learning SARS-CoV-2 Adolescent Humans Artificial Intelligence Pandemics COVID-19
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A fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis.

The European respiratory journal Aug 6, 2020
Coronavirus disease 2019 (COVID-19) has spread globally, and medical resources become insufficient in many regions. Fast diagnosis of COVID-19 and finding high-risk patients with worse prognosis for early prevention and medical resource optimisation ...
Pandemics COVID-19 Prognosis Retrospective Studies Tomography, X-Ray Computed Humans Area Under Curve Coronavirus Infections Automation Lung Diseases, Fungal Pneumonia, Bacterial Betacoronavirus Pneumonia, Viral Male Pneumonia, Mycoplasma Middle Aged Lung Deep Learning Image Processing, Computer-Assisted Female SARS-CoV-2 Aged Adult
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Using machine learning algorithms to review computed tomography scans and assess risk for cardiovascular disease: Retrospective analysis from the National Lung Screening Trial (NLST).

PloS one Aug 3, 2020
BACKGROUND: The National Lung Screening Trial (NLST) demonstrated that annual screening with low dose CT in high-risk population was associated with reduction in lung cancer mortality. Nonetheless, the leading cause of mortality in the study was from...
Lung Lung Neoplasms Fatty Liver United States Mass Screening Early Detection of Cancer Humans Cigarette Smoking Male Liver Machine Learning Coronary Vessels Randomized Controlled Trials as Topic Cardiovascular Diseases Retrospective Studies Clinical Trials, Phase III as Topic Middle Aged Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed National Cancer Institute (U.S.) Risk Assessment Emphysema Female Risk Factors
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ADR-Net: Context extraction network based on M-Net for medical image segmentation.

Medical physics Aug 2, 2020
PURPOSE: Medical image segmentation is an essential component of medical image analysis. Accurate segmentation can assist doctors in diagnosis and relieve their fatigue. Although several image segmentation methods based on U-Net have been proposed, t...
Neural Networks, Computer Lung Image Processing, Computer-Assisted
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Artificial Intelligence in Lung Cancer: Bridging the Gap Between Computational Power and Clinical Decision-Making.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Jul 31, 2020
Lung cancer remains the most common cause of cancer death worldwide. Recent advances in lung cancer screening, radiotherapy, surgical techniques, and systemic therapy have led to increasing complexity in diagnosis, treatment decision-making, and asse...
Artificial Intelligence Clinical Decision-Making Lung Lung Neoplasms Diagnostic Imaging Image Interpretation, Computer-Assisted Humans
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A robust convolutional neural network for lung nodule detection in the presence of foreign bodies.

Scientific reports Jul 31, 2020
Lung cancer is a major cause of death worldwide. As early detection can improve outcome, regular screening is of great interest, especially for certain risk groups. Besides low-dose computed tomography, chest X-ray is a potential option for screening...
Solitary Pulmonary Nodule False Positive Reactions Foreign Bodies Humans Neural Networks, Computer Tomography, X-Ray Computed Lung
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Application of a Robotic Tele-Echography System for COVID-19 Pneumonia.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine Jul 29, 2020
To date, coronavirus disease 2019 (COVID-19) has infected millions of people worldwide. Ultrasound plays an indispensable role in the diagnosis, monitoring, and follow-up of patients with COVID-19. In this study, we used a robotic tele-echography sys...
Humans Quarantine Ultrasonography COVID-19 Venous Thrombosis Aged, 80 and over Telemedicine SARS-CoV-2 Lower Extremity Male Robotics Disease Progression Heart Lung
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