AIMC Topic: Lung

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Deep learning diagnostic and severity-stratification for interstitial lung diseases and chronic obstructive pulmonary disease in digital lung auscultations and ultrasonography: clinical protocol for an observational case-control study.

BMC pulmonary medicine Jun 2, 2023
BACKGROUND: Interstitial lung diseases (ILD), such as idiopathic pulmonary fibrosis (IPF) and non-specific interstitial pneumonia (NSIP), and chronic obstructive pulmonary disease (COPD) are severe, progressive pulmonary disorders with a poor prognos...
Ultrasonography Observational Studies as Topic Idiopathic Pulmonary Fibrosis Case-Control Studies Deep Learning Respiratory Sounds Clinical Protocols Idiopathic Interstitial Pneumonias Artificial Intelligence Lung Diseases, Interstitial Adult Humans Auscultation Quality of Life Pulmonary Disease, Chronic Obstructive Lung
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Two- Versus 8-Zone Lung Ultrasound in Heart Failure: Analysis of a Large Data Set Using a Deep Learning Algorithm.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine May 31, 2023
OBJECTIVE: Scanning protocols for lung ultrasound often include 8 or more lung zones, which may limit real-world clinical use. We sought to compare a 2-zone, anterior-superior thoracic ultrasound protocol for B-line artifact detection with an 8-zone ...
Adult Lung Ultrasonography Pulmonary Edema Deep Learning Humans Heart Failure
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Target-oriented deep learning-based image registration with individualized test-time adaptation.

Medical physics May 24, 2023
BACKGROUND: A classic approach in medical image registration is to formulate an optimization problem based on the image pair of interest, and seek a deformation vector field (DVF) to minimize the corresponding objective, often iteratively. It has a c...
Algorithms Image Processing, Computer-Assisted Lung Humans Deep Learning
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Deep learning to estimate lung disease mortality from chest radiographs.

Nature communications May 16, 2023
Prevention and management of chronic lung diseases (asthma, lung cancer, etc.) are of great importance. While tests are available for reliable diagnosis, accurate identification of those who will develop severe morbidity/mortality is currently limite...
Radiography, Thoracic Thorax Deep Learning Lung Lung Diseases Humans
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Artificially-generated consolidations and balanced augmentation increase performance of U-net for lung parenchyma segmentation on MR images.

PloS one May 9, 2023
PURPOSE: To improve automated lung segmentation on 2D lung MR images using balanced augmentation and artificially-generated consolidations for training of a convolutional neural network (CNN).
Semantic Web Lung Humans Healthy Volunteers Neural Networks, Computer Thorax
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Deep learning for diagnosis of malign pleural effusion on computed tomography images.

Clinics (Sao Paulo, Brazil) May 5, 2023
BACKGROUND: The pleura is a serous membrane that surrounds the lungs. The visceral surface secretes fluid into the serous cavity and the parietal surface ensures a regular absorption of this fluid. If this balance is disturbed, fluid accumulation occ...
Humans Lung Deep Learning Tomography, X-Ray Computed Pleural Effusion Pleural Effusion, Malignant
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Application of an artificial intelligence ensemble for detection of important secondary findings on lung ventilation and perfusion SPECT-CT.

Clinical imaging May 2, 2023
RATIONALE: Single-photon-emission-computerized-tomography/computed-tomography(SPECT/CT) is commonly used for pulmonary disease. Scant work has been done to determine ability of AI for secondary findings using low-dose-CT(LDCT) attenuation correction ...
Perfusion Tomography, Emission-Computed, Single-Photon Tomography, X-Ray Computed Reproducibility of Results Lung Calcium Dilatation, Pathologic Humans Artificial Intelligence Retrospective Studies
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Collimation border with U-Net segmentation on chest radiographs compared to radiologists.

Radiography (London, England : 1995) May 2, 2023
INTRODUCTION: Chest Radiography (CXR) is a common radiographic procedure. Radiation exposure to patients should be kept as low as reasonably achievable (ALARA), and monitored continuously as part of quality assurance (QA) programs. One of the most ef...
Humans Neural Networks, Computer Algorithms Radiologists Lung Radiography
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MuRCL: Multi-Instance Reinforcement Contrastive Learning for Whole Slide Image Classification.

IEEE transactions on medical imaging May 2, 2023
Multi-instance learning (MIL) is widely adop- ted for automatic whole slide image (WSI) analysis and it usually consists of two stages, i.e., instance feature extraction and feature aggregation. However, due to the "weak supervision" of slide-level l...
Humans Lung Supervised Machine Learning Datasets as Topic Image Processing, Computer-Assisted Kidney
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A deep learning-based application for COVID-19 diagnosis on CT: The Imaging COVID-19 AI initiative.

PloS one May 2, 2023
BACKGROUND: Recently, artificial intelligence (AI)-based applications for chest imaging have emerged as potential tools to assist clinicians in the diagnosis and management of patients with coronavirus disease 2019 (COVID-19).
Cohort Studies COVID-19 Testing Humans Artificial Intelligence COVID-19 Tomography, X-Ray Computed Lung Male SARS-CoV-2 Deep Learning Female Middle Aged
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