AIMC Topic: X-Rays

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AXEAP: a software package for X-ray emission data analysis using unsupervised machine learning.

Journal of synchrotron radiation Jul 21, 2022
The Argonne X-ray Emission Analysis Package (AXEAP) has been developed to calibrate and process X-ray emission spectroscopy (XES) data collected with a two-dimensional (2D) position-sensitive detector. AXEAP is designed to convert a 2D XES image into...
Radiography X-Rays Data Analysis Unsupervised Machine Learning Software
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Automated diagnosis and prognosis of COVID-19 pneumonia from initial ER chest X-rays using deep learning.

BMC infectious diseases Jul 21, 2022
BACKGROUND: Airspace disease as seen on chest X-rays is an important point in triage for patients initially presenting to the emergency department with suspected COVID-19 infection. The purpose of this study is to evaluate a previously trained interp...
COVID-19 Prognosis Humans Artificial Intelligence SARS-CoV-2 Adult Deep Learning Retrospective Studies Tomography, X-Ray Computed Radiography, Thoracic X-Rays
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An efficient deep learning-based framework for tuberculosis detection using chest X-ray images.

Tuberculosis (Edinburgh, Scotland) Jul 19, 2022
Early diagnosis of tuberculosis (TB) is an essential and challenging task to prevent disease, decrease mortality risk, and stop transmission to other people. The chest X-ray (CXR) is the top choice for lung disease screening in clinics because it is ...
Deep Learning Pneumonia Mycobacterium tuberculosis X-Rays Tuberculosis Neural Networks, Computer COVID-19 Humans
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KUB-UNet: Segmentation of Organs of Urinary System from a KUB X-ray Image.

Computer methods and programs in biomedicine Jul 17, 2022
PURPOSE: The alarming increase in diseases of urinary system is a cause of concern for the populace and health experts. The traditional techniques used for the diagnosis of these diseases are inconvenient for patients, require high cost, and addition...
X-Rays Artificial Intelligence Tomography, X-Ray Computed Image Processing, Computer-Assisted Kidney Reproducibility of Results Humans
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Use data augmentation for a deep learning classification model with chest X-ray clinical imaging featuring coal workers' pneumoconiosis.

BMC pulmonary medicine Jul 15, 2022
PURPOSE: This paper aims to develop a successful deep learning model with data augmentation technique to discover the clinical uniqueness of chest X-ray imaging features of coal workers' pneumoconiosis (CWP).
Deep Learning Coal Mining Pneumoconiosis Coal X-Rays Anthracosis Humans Prospective Studies
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COVID-19 Classification from Chest X-Ray Images: A Framework of Deep Explainable Artificial Intelligence.

Computational intelligence and neuroscience Jul 14, 2022
COVID-19 detection and classification using chest X-ray images is a current hot research topic based on the important application known as medical image analysis. To halt the spread of COVID-19, it is critical to identify the infection as soon as pos...
COVID-19 Testing COVID-19 Humans X-Rays Deep Learning Artificial Intelligence
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Feature-level ensemble approach for COVID-19 detection using chest X-ray images.

PloS one Jul 14, 2022
Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), also known as the coronavirus disease 2019 (COVID-19), has threatened many human beings around the world and capsized economies at unprecedented magnitudes. Therefore, the detection of thi...
Deep Learning X-Rays COVID-19 SARS-CoV-2 Humans Neural Networks, Computer
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Non-iterative learning machine for identifying CoViD19 using chest X-ray images.

Scientific reports Jul 13, 2022
CoViD19 is a novel disease which has created panic worldwide by infecting millions of people around the world. The last significant variant of this virus, called as omicron, contributed to majority of cases in the third wave across globe. Though less...
Neural Networks, Computer COVID-19 Humans Radiography Thorax X-Rays SARS-CoV-2 Deep Learning
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Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-ray Data.

Sensors (Basel, Switzerland) Jul 11, 2022
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for...
Neural Networks, Computer ROC Curve Humans Radiography Privacy X-Rays
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PCA-Based Incremental Extreme Learning Machine (PCA-IELM) for COVID-19 Patient Diagnosis Using Chest X-Ray Images.

Computational intelligence and neuroscience Jul 4, 2022
Novel coronavirus 2019 has created a pandemic and was first reported in December 2019. It has had very adverse consequences on people's daily life, healthcare, and the world's economy as well. According to the World Health Organization's most recent ...
COVID-19 SARS-CoV-2 X-Rays Deep Learning Humans Pandemics
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