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

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 …

In domains such as medical and healthcare, the interpretability and explainability of
machine learning and artificial intelligence systems are crucial for building trust in their …

The quest to open black box artificial intelligence (AI) systems evolved into an emerging
phenomenon of global interest for academia, business, and society and brought about the …

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 …

Recently proposed legal frameworks for Artificial Intelligence (AI) depart from some
frameworks of concepts regarding ethical and trustworthy AI that provide the technical …

Accurate predictions of building energy consumption are essential for reducing the energy
performance gap. While data-driven energy quantification methods based on machine …

This systematic literature review examines state-of-the-art Explainable Artificial Intelligence
(XAI) methods applied to medical image analysis, discussing current challenges and future …

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

Timely diagnosis of brain tumors using MRI and its potential impact on patient survival are
critical issues addressed in this study. Traditional DL models often lack transparency …