With an increase in deep learning-based methods, the call for explainability of such methods
grows, especially in high-stakes decision making areas such as medical image analysis …

Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease
diagnosis with their outstanding image classification performance. In spite of the outstanding …

Despite the myriad peer-reviewed papers demonstrating novel Artificial Intelligence (AI)-
based solutions to COVID-19 challenges during the pandemic, few have made a significant …

In this paper, we propose a vision-language pre-training model, Clinical-BERT, for the
medical domain, and devise three domain-specific tasks: Clinical Diagnosis (CD), Masked …

As one of the most common diabetic complications, diabetic retinopathy (DR) can cause
retinal damage, vision loss and even blindness. Automated DR grading technology has …

Researchers seek help from deep learning methods to alleviate the enormous burden of
reading radiological images by clinicians during the COVID-19 pandemic. However …

Deep learning approaches have demonstrated remarkable progress in automatic Chest X-
ray analysis. The data-driven feature of deep models requires training data to cover a large …

Purpose Wireless capsule endoscopy (WCE) is a fundamental diagnosing tool for gastro-
intestinal (GI) lesion detection. Detecting and locating the lesions in WCE images using a …

Automated multi-label chest X-ray (CXR) image classification has recently made significant
progress in clinical diagnosis based on the advanced deep learning techniques. However …

Over the last decade, deep learning (DL) has contributed to a paradigm shift in computer
vision and image recognition creating widespread opportunities of using artificial …