A ensemble methodology for automatic classification of chest X-rays using deep learning

L Vogado, F Araújo, PS Neto, J Almeida… - Computers in Biology …, 2022 - Elsevier
Chest radiographies, or chest X-rays, are the most standard imaging exams used in daily
hospitals. Responsible for assisting in detecting numerous pathologies and findings that …

Computer-aided diagnostic for classifying chest X-ray images using deep ensemble learning

L Visuña, D Yang, J Garcia-Blas, J Carretero - BMC Medical Imaging, 2022 - Springer
Background Nowadays doctors and radiologists are overwhelmed with a huge amount of
work. This led to the effort to design different Computer-Aided Diagnosis systems (CAD …

Utilization of deep convolutional neural networks for accurate chest X-ray diagnosis and disease detection

M Mann, RP Badoni, H Soni, M Al-Shehri… - Interdisciplinary …, 2023 - Springer
Chest radiography is a widely used diagnostic imaging procedure in medical practice, which
involves prompt reporting of future imaging tests and diagnosis of diseases in the images. In …

AI-driven deep convolutional neural networks for chest X-ray pathology identification

S Albahli… - Journal of X-Ray Science …, 2022 - content.iospress.com
BACKGROUND: Chest X-ray images are widely used to detect many different lung diseases.
However, reading chest X-ray images to accurately detect and classify different lung …

[PDF][PDF] Development of a deep learning model for chest X-ray screening

WH Hsu, FJ Tsai, G Zhang, CK Chang… - MEDICAL PHYSICS …, 2019 - researchgate.net
Developed in recent years, deep neural network becomes the best method for rapid analysis
of advanced features and automation in medical image analysis. As a second clinical …

Convolutional neural networks for the classification of chest X-rays in the IoT era

K Almezhghwi, S Serte, F Al-Turjman - Multimedia tools and applications, 2021 - Springer
Chest X-ray medical imaging technology allows the diagnosis of many lung diseases. It is
known that this technology is frequently used in hospitals, and it is the most accurate way of …

Convolutional neural network to detect thorax diseases from multi-view chest X-rays

MMA Monshi, J Poon, V Chung - … , NSW, Australia, December 12–15, 2019 …, 2019 - Springer
Chest radiography is the most common examination for a radiologist. This demands correct
and immediate diagnosis of a patient's thorax to avoid life threatening diseases. Not only …

Radbot-cxr: Classification of four clinical finding categories in chest x-ray using deep learning

C Brestel, R Shadmi, I Tamir… - Medical Imaging with …, 2018 - openreview.net
The well-documented global shortage of radiologists is most acutely manifested in countries
where the rapid rise of a middle class has created a new capacity to produce imaging …

Role of an automated deep learning algorithm for reliable screening of abnormality in chest radiographs: a prospective multicenter quality improvement study

A Govindarajan, A Govindarajan, S Tanamala… - Diagnostics, 2022 - mdpi.com
In medical practice, chest X-rays are the most ubiquitous diagnostic imaging tests. However,
the current workload in extensive health care facilities and lack of well-trained radiologists is …

Classification and Prediction of Lung Diseases According to Chest Radiography

RI Dumaev, SA Molodyakov - 2023 IV International Conference …, 2023 - ieeexplore.ieee.org
Chest X-ray is a widely used and cost-effective medical imaging procedure, but its
effectiveness is limited due to the shortage of qualified radiologists. Interest in deep learning …