The purpose of this review is integrating and contextualizing relevant literature on the factors
influencing the adoption of AI in the healthcare industry into a comprehensive framework …

Objectives This review study was aimed to identify and document organizational,
professional, and patient characteristics influencing the adoption of Artificial Intelligence (AI) …

Background Artificial intelligence (AI) for healthcare presents potential solutions to some of
the challenges faced by health systems around the world. However, it is well established in …

The field of eXplainable Artificial Intelligence (XAI) focuses on providing explanations for AI
systems' decisions. XAI applications to AI-based Clinical Decision Support Systems (DSS) …

Artificial intelligence-based clinical diagnostic decision support systems promise
transformational improvements in doctors' efficiency and accuracy. Nevertheless, low …

Artificial intelligence (AI) and AI-based chatbots, such as ChatGPT, are transforming the
approach to education. In particular, ChatGPT's potential to process large amounts of data …

Artificial Intelligence (AI) technology is transforming the healthcare sector. However, despite
this, the associated ethical implications remain open to debate. This research investigates …

eXplainable AI (XAI) involves two intertwined but separate challenges: the development of
techniques to extract explanations from black-box AI models and the way such explanations …

Introduction Despite the proliferation of Artificial Intelligence (AI) technology over the last
decade, clinician, patient, and public perceptions of its use in healthcare raise a number of …

Healthcare communication is the lifeblood of effective patient care. The ability of patients
and providers to exchange information, comprehends diagnoses, and collaboratively make …