AIMC Topic: Lung Diseases

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A Novel Approach to the Technique of Lung Region Segmentation Based on a Deep Learning Model to Diagnose COVID-19 X-ray Images.

Current medical imaging Jan 1, 2024
BACKGROUND: The novel coronavirus pandemic has caused a global health crisis, placing immense strain on healthcare systems worldwide. Chest X-ray technology has emerged as a critical tool for the diagnosis and treatment of COVID-19. However, the manu...
Lung Deep Learning Pneumonia Lung Diseases Humans X-Rays Pandemics COVID-19
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Chest CT Image based Lung Disease Classification - A Review.

Current medical imaging Jan 1, 2024
Computed tomography (CT) scans are widely used to diagnose lung conditions due to their ability to provide a detailed overview of the body's respiratory system. Despite its popularity, visual examination of CT scan images can lead to misinterpretatio...
Lung Deep Learning Lung Neoplasms Lung Diseases Humans Machine Learning Tomography, X-Ray Computed
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Deep Learning-based Classification of Fibrotic Lung Disease: Can Computer Vision See the Future?

American journal of respiratory and critical care medicine Oct 1, 2022
Humans Machine Learning Computers Tomography, X-Ray Computed Deep Learning Lung Diseases
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Are rib fractures stable? An analysis of progressive rib fracture offset in the acute trauma setting.

The journal of trauma and acute care surgery Dec 1, 2021
BACKGROUND: Rib fractures serve as both a marker of injury severity and a guide for clinical decision making for trauma patients. Although recent studies have suggested that rib fractures are dynamic, the degree of progressive offset remains unknown....
Humans Neural Networks, Computer Rib Fractures Clinical Decision-Making Female Male Middle Aged Thoracic Injuries Retrospective Studies Tomography, X-Ray Computed Flail Chest Outcome Assessment, Health Care Quality Improvement Injury Severity Score Trauma Centers Disease Progression Patient Care Lung Diseases
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Evaluation of a deep learning-based computer-aided detection algorithm on chest radiographs: Case-control study.

Medicine Apr 23, 2021
Along with recent developments in deep learning techniques, computer-aided diagnosis (CAD) has been growing rapidly in the medical imaging field. In this work, we evaluate the deep learning-based CAD algorithm (DCAD) for detecting and localizing 3 ma...
Pneumothorax Lung Diseases Observer Variation Radiography, Thoracic Case-Control Studies Deep Learning ROC Curve Lung Neoplasms Thoracic Neoplasms Area Under Curve Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Aged Male Humans Middle Aged Female
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A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
Unplanned hospital readmissions are a burden to patients and increase healthcare costs. A wide variety of machine learning (ML) models have been suggested to predict unplanned hospital readmissions. These ML models were often specifically trained on ...
Humans Datasets as Topic Machine Learning Cohort Studies Treatment Outcome Area Under Curve Hospitalization Models, Statistical Prognosis Tertiary Care Centers Male Chronic Disease Electronic Health Records Lung Diseases Cardiovascular Diseases Female Patient Readmission Neoplasms
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Artificial Intelligence Algorithm Detecting Lung Infection in Supine Chest Radiographs of Critically Ill Patients With a Diagnostic Accuracy Similar to Board-Certified Radiologists.

Critical care medicine Jul 1, 2020
OBJECTIVES: Interpretation of lung opacities in ICU supine chest radiographs remains challenging. We evaluated a prototype artificial intelligence algorithm to classify basal lung opacities according to underlying pathologies.
Radiologists Humans Lung Diseases Artificial Intelligence Image Interpretation, Computer-Assisted Algorithms Female Radiography, Thoracic Reproducibility of Results Supine Position Retrospective Studies Male Tomography, X-Ray Computed Middle Aged Critical Illness
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Machine Learning/Deep Neuronal Network: Routine Application in Chest Computed Tomography and Workflow Considerations.

Journal of thoracic imaging May 1, 2020
The constantly increasing number of computed tomography (CT) examinations poses major challenges for radiologists. In this article, the additional benefits and potential of an artificial intelligence (AI) analysis platform for chest CT examinations i...
Neural Networks, Computer Radiography, Thoracic Radiographic Image Interpretation, Computer-Assisted Machine Learning Humans Tomography, X-Ray Computed Workflow Lung Lung Diseases
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Deep Learning for Pulmonary Image Analysis: Classification, Detection, and Segmentation.

Advances in experimental medicine and biology Jan 1, 2020
Image-based computer-aided diagnosis (CAD) algorithms by the use of convolutional neural network (CNN) which do not require the image-feature extractor are powerful compared with conventional feature-based CAD algorithms which require the image-featu...
Lung Diseases Image Interpretation, Computer-Assisted Humans Lung Diagnosis, Computer-Assisted Deep Learning
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Generalizable Inter-Institutional Classification of Abnormal Chest Radiographs Using Efficient Convolutional Neural Networks.

Journal of digital imaging Oct 1, 2019
Our objective is to evaluate the effectiveness of efficient convolutional neural networks (CNNs) for abnormality detection in chest radiographs and investigate the generalizability of our models on data from independent sources. We used the National ...
Lung Diseases Male Datasets as Topic Middle Aged Humans Deep Learning Radiography, Thoracic Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted Female
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