The MIMIC-CXR dataset includes over 200,000 chest X-ray images, representing a diverse range of chest diseases, such as pneumonia, tuberculosis, and pneumothorax, with the majority of the images ...

As the number of people with allergies grows worldwide, scientists are trying to work out precisely how and why these conditions—such as asthma and eczema—develop.

Self-supervised learning (SSL) reduces the need for manual annotation in deep learning models for medical image analysis. By learning the representations from unablelled data, self-supervised models ...

Patients with bronchial asthma (Group A) were further subdivided into 3 subgroups according to severity of asthma {25 patients had mild asthma, 23 patients had moderate asthma, and 12 patients had ...

The automatic diagnosis of chest diseases is a popular and challenging task. Most current methods are based on convolutional neural networks (CNNs), which focus on local features while neglecting ...