In this review, we address the issue of fairness in the clinical integration of artificial
intelligence (AI) in the medical field. As the clinical adoption of deep learning algorithms, a …

Objective The attitudes about the usage of artificial intelligence in healthcare are
controversial. Unlike the perception of healthcare professionals, the attitudes of patients and …

Developing and evaluating statistical prediction models is challenging, and many pitfalls can
arise. This article identifies what the authors feel are some common methodological …

Background Artificial intelligence (AI) has repeatedly been shown to encode historical
inequities in healthcare. We aimed to develop a framework to quantitatively assess the …

Background Prediction calculators can help set outcomes expectations following
orthopaedic surgery, however effective implementation strategies for these tools are …

Welfare measures overall utility across a population, whereas malfare measures overall
disutility, and the social planner's problem can be cast either as maximizing the former or …

Objective: Controversy exists around the world as experts disagree on what artificial
intelligence will imply for humanity in the future. Medical experts are starting to share …

The world is abuzz with applications of machine learning and data science in almost every
field: commerce, transportation, banking, and more recently, healthcare. Breakthroughs in …

Objectives The application of artificial intelligence (AI) in healthcare is an important public
health issue. However, few studies have investigated the perceptions and attitudes of …

INTRODUCTION Artificial intelligence (AI) systems such as machine learning hold great
promise for use in various sectors and policy areas. In particular, recent developments in …