In this study, multiple lung diseases are diagnosed with the help of the Neural Network
algorithm. Specifically, Emphysema, Infiltration, Mass, Pleural Thickening, Pneumonia …

Numerous epidemic lung diseases such as COVID-19, tuberculosis (TB), and pneumonia
have spread over the world, killing millions of people. Medical specialists have experienced …

Limitations of the chest X-ray (CXR) have resulted in attempts to create machine learning
systems to assist clinicians and improve interpretation accuracy. An understanding of the …

Chest X-ray is an essential diagnostic tool in the identification of chest diseases given its
high sensitivity to pathological abnormalities in the lungs. However, image-driven diagnosis …

Over the last few years, convolutional neural networks (CNNs) have dominated the field of
computer vision thanks to their ability to extract features and their outstanding performance …

The image reconstruction of electrical impedance tomography (EIT) is a nonlinear ill-posed
inverse problem, and the reconstructed images tend to have artifacts due to noise in the …

In the realm of medical diagnostics, particularly in differential diagnosis, where differentiating
between illnesses or ailments with comparable symptoms is essential, deep learning has …

Abstract Key Smart City applications such as traffic management and public security rely
heavily on the intelligent processing of video and image data, often in the form of visual …

With an escalating arms race to adopt machine learning (ML) into diverse application
domains, there is an urgent need to efficiently support distributed machine learning (ML) …

Early diagnosis of lung conditions is crucial for effective treatment and improving patient
health. However, traditional diagnostic methods using chest X-ray images have some …