Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …

The black-box nature of current artificial intelligence (AI) has caused some to question
whether AI must be explainable to be used in high-stakes scenarios such as medicine. It has …

Background Explainability is one of the most heavily debated topics when it comes to the
application of artificial intelligence (AI) in healthcare. Even though AI-driven systems have …

Artificial intelligence (AI) models for decision support have been developed for clinical
settings such as radiology, but little work evaluates the potential impact of such systems. In …

Clinical oncology is experiencing rapid growth in data that are collected to enhance cancer
care. With recent advances in the field of artificial intelligence (AI), there is now a …

Although decision‐making algorithms are not new to medicine, the availability of vast stores
of medical data, gains in computing power, and breakthroughs in machine learning are …

In recent years, improved artificial intelligence (AI) algorithms and access to training data
have led to the possibility of AI augmenting or replacing some of the current functions of …

This study reflects on proliferating ethical initiatives, with an eye on social good in the
healthcare industry context while leveraging innovative digital technological infrastructures …

In an age where technology is evolving at a sometimes incomprehensibly rapid pace, the
liver community must adjust and learn to embrace breakthroughs with an open mind in order …

Abstract The advancement of Artificial Intelligence (AI) and Machine Learning (ML) has
profound implications for both the utility and security of our digital interactions. This paper …