This article presents a systematic mapping study dedicated to conduct a literature review on
machine learning and IoT applied in the identification of diseases through heart sounds …

This paper presents research on how knowledge brokers attempt to translate opaque
algorithmic predictions. The research is based on a 31-month ethnographic study of the …

Introduction Radiographer reporting is accepted practice in the UK. With a national shortage
of radiographers and radiologists, artificial intelligence (AI) support in reporting may help …

While the self-learning nature of AI systems that use machine learning calls for sustained co-
creation between developers and users during development, implementation and use …

Purpose This paper focuses on how the implementation of artificial intelligence algorithms
(AI) challenges and changes the existing communication practice in radiology seen from a …

Over the past decade, there has been a dramatic rise in the interest relating to the
application of artificial intelligence (AI) in radiology. Originally only 'narrow'AI tasks were …

Objective Despite the widespread recognition of the importance of artificial intelligence (AI)
in healthcare, its implementation is often limited. This article aims to address this …

Digital pathology is an image-based environment for the acquisition, management, sharing,
and interpretation of pathology information supported by techniques for data extraction and …

La radiologie est l'un des premiers secteurs médicaux à être concerné concrètement par
l'arrivée de dispositifs labellisés «intelligence artificielle» pour le traitement des images …

Artificial Intelligence (AI) is being rapidly introduced into the workplace, creating debate
around what AI means for our work and organizations. This book gives grounded …