As artificial intelligence (AI) continues to make significant advancements in healthcare, there
is a growing need to ensure the transparency and trustworthiness of AI-driven clinical …

Artificial intelligence (AI) studies are progressing at a breakneck pace, with prospective
programs in healthcare industries being established. In healthcare, there has been an …

XAI refers to the techniques and methods for building AI applications which assist end users
to interpret output and predictions of AI models. Black box AI applications in high-stakes …

Machine Learning and Artificial Intelligence (AI) more broadly have great immediate and
future potential for transforming almost all aspects of medicine. However, in many …

Artificial intelligence (AI) models are increasingly finding applications in the field of
medicine. Concerns have been raised about the explainability of the decisions that are …

Artificial Intelligence in Medicine has made significant progress with emerging applications
in medical imaging, patient care, and other areas. While these applications have proven …

Background and objectives Artificial intelligence (AI) has branched out to various
applications in healthcare, such as health services management, predictive medicine …

Abstract Explainable Artificial Intelligence (XAI) encompasses the strategies and
methodologies used in constructing AI systems that enable end-users to comprehend and …

The use of artificial intelligence (AI) systems in biomedical and clinical settings can disrupt
the traditional doctor–patient relationship, which is based on trust and transparency in …

AI has changed many industries, including healthcare, by giving doctors and researchers
better ways to predict and diagnose diseases. But the lack of transparency in AI models …