AI Medical Compendium Topic:
Lung

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Artificial Intelligence Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Origin at Chest CT.

Radiology Apr 27, 2020
Background Coronavirus disease 2019 (COVID-19) and pneumonia of other diseases share similar CT characteristics, which contributes to the challenges in differentiating them with high accuracy. Purpose To establish and evaluate an artificial intellige...
Pandemics COVID-19 Retrospective Studies Tomography, X-Ray Computed Female Infant, Newborn Humans Artificial Intelligence Rhode Island Betacoronavirus Pneumonia, Viral China Adolescent Child, Preschool Child Diagnosis, Differential Pneumonia Radiologists Coronavirus Infections Radiography, Thoracic Philadelphia SARS-CoV-2 Aged Aged, 80 and over Sensitivity and Specificity Young Adult Male Adult Middle Aged Infant Lung
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Classification of COVID-19 patients from chest CT images using multi-objective differential evolution-based convolutional neural networks.

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology Apr 27, 2020
Early classification of 2019 novel coronavirus disease (COVID-19) is essential for disease cure and control. Compared with reverse-transcription polymerase chain reaction (RT-PCR), chest computed tomography (CT) imaging may be a significantly more tr...
Pandemics COVID-19 Tomography, X-Ray Computed Image Interpretation, Computer-Assisted Lung SARS-CoV-2 False Negative Reactions Sensitivity and Specificity Deep Learning False Positive Reactions Humans Clinical Laboratory Techniques Reverse Transcriptase Polymerase Chain Reaction Neural Networks, Computer Coronavirus Infections Betacoronavirus COVID-19 Testing Pneumonia, Viral
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Towards large-scale case-finding: training and validation of residual networks for detection of chronic obstructive pulmonary disease using low-dose CT.

The Lancet. Digital health Apr 21, 2020
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is underdiagnosed in the community. Thoracic CT scans are widely used for diagnostic and screening purposes for lung cancer. In this proof-of-concept study, we aimed to evaluate a software pipe...
Mass Screening Area Under Curve Models, Biological Smoking Smokers Ex-Smokers Cohort Studies ROC Curve Image Processing, Computer-Assisted Lung Neoplasms Canada Male Middle Aged Risk Assessment Disease Progression Lung Humans Neural Networks, Computer Female Aged Pulmonary Disease, Chronic Obstructive Artificial Intelligence Data Analysis Tomography, X-Ray Computed
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Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.

European radiology Mar 28, 2020
OBJECTIVES: We develop and validate a radiomics model based on multiparametric magnetic resonance imaging (MRI) in the classification of the pulmonary lesion and identify optimal machine learning methods.
Cohort Studies ROC Curve Support Vector Machine Lung Diseases Multiparametric Magnetic Resonance Imaging Young Adult Adult Male Middle Aged Lung Humans Machine Learning Retrospective Studies Female Aged
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Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study.

European radiology Mar 11, 2020
OBJECTIVES: Pneumothorax is the most common and potentially life-threatening complication arising from percutaneous lung biopsy. We evaluated the performance of a deep learning algorithm for detection of post-biopsy pneumothorax in chest radiographs ...
Humans Algorithms Retrospective Studies Female Aged Radiography, Thoracic Biopsy, Needle Pneumothorax Deep Learning Adult Cohort Studies Sensitivity and Specificity ROC Curve Male Area Under Curve Middle Aged Radiologists Lung
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Supervised and unsupervised language modelling in Chest X-Ray radiological reports.

PloS one Mar 10, 2020
Chest radiography (CXR) is the most commonly used imaging modality and deep neural network (DNN) algorithms have shown promise in effective triage of normal and abnormal radiograms. Typically, DNNs require large quantities of expertly labelled traini...
Radiography Humans Lung Diseases Neural Networks, Computer Supervised Machine Learning Lung Datasets as Topic Decision Support Systems, Clinical Image Processing, Computer-Assisted
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Deep learning approach to classification of lung cytological images: Two-step training using actual and synthesized images by progressive growing of generative adversarial networks.

PloS one Mar 5, 2020
Cytology is the first pathological examination performed in the diagnosis of lung cancer. In our previous study, we introduced a deep convolutional neural network (DCNN) to automatically classify cytological images as images with benign or malignant ...
Male Humans Data Accuracy Lung Image Interpretation, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Lung Neoplasms
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Calculating the target exposure index using a deep convolutional neural network and a rule base.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Feb 27, 2020
PURPOSE: The objective of this study is to determine the quality of chest X-ray images using a deep convolutional neural network (DCNN) and a rule base without performing any visual assessment. A method is proposed for determining the minimum diagnos...
Middle Aged Lung Deep Learning Image Processing, Computer-Assisted Spine Aged Aged, 80 and over Young Adult Adult Sensitivity and Specificity Radiography, Thoracic Thorax Mediastinum Humans Neural Networks, Computer Tomography, X-Ray Computed Reproducibility of Results
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LungRegNet: An unsupervised deformable image registration method for 4D-CT lung.

Medical physics Feb 26, 2020
PURPOSE: To develop an accurate and fast deformable image registration (DIR) method for four-dimensional computed tomography (4D-CT) lung images. Deep learning-based methods have the potential to quickly predict the deformation vector field (DVF) in ...
Humans Lung Image Processing, Computer-Assisted Unsupervised Machine Learning Four-Dimensional Computed Tomography
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Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Feb 17, 2020
BACKGROUND: The purpose of this study was to build radiogenomics models from texture signatures derived from computed tomography (CT) and F-FDG PET-CT (FDG PET-CT) images of non-small cell lung cancer (NSCLC) with and without epidermal growth factor ...
Lung Lung Neoplasms Carcinoma, Non-Small-Cell Lung Predictive Value of Tests Positron Emission Tomography Computed Tomography Imaging Genomics Humans Mutation Female Machine Learning Radiopharmaceuticals Reproducibility of Results Retrospective Studies Image Interpretation, Computer-Assisted Aged Fluorodeoxyglucose F18 Sensitivity and Specificity ErbB Receptors Male
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