Healthcare systems are under increasing strain due to a myriad of factors, from a steadily
ageing global population to the current COVID-19 pandemic. In a world where we have …

Convolutional neural networks (CNNs) constitute a widely used deep learning approach that
has frequently been applied to the problem of brain tumor diagnosis. Such techniques still …

Rational Deep learning (DL) has demonstrated a remarkable performance in diagnostic
imaging for various diseases and modalities and therefore has a high potential to be used …

Kidney abnormality is one of the major concerns in modern society, and it affects millions of
people around the world. To diagnose different abnormalities in human kidneys, a narrow …

Utilization of model-agnostic explainable artificial intelligence frameworks in oncology: a
narrative review - PMC Back to Top Skip to main content NIH NLM Logo Access keys NCBI …

COVID-19 has caused over 528 million infected cases and over 6.25 million deaths since its
outbreak in 2019. The uncontrolled transmission of the SARS-CoV-2 virus has caused …

Deepfake technology uses auto-encoders and generative adversarial networks to replace or
artificially construct fine-tuned faces, emotions, and sounds. Although there have been …

Abstract Purpose To review eXplainable Artificial Intelligence/(XAI) methods available for
medical imaging/(MI). Method A scoping review was conducted following the Joanna Briggs …

Convolutional neural networks (CNNs) are deep learning models used widely for solving
various tasks like computer vision and speech recognition. CNNs are developed manually …

As black-box machine learning models become more complex and are applied in high-
stakes settings, the need for providing explanations for their predictions becomes crucial …