Artificial intelligence (AI) stands at the threshold of revolutionizing clinical oncology, with
considerable potential to improve early cancer detection and risk assessment, and to enable …

The growing use of digital technologies (DTs) has a myriad of implications to socio-technical
systems, which are not yet fully recognised. This paper investigates the contributions and …

Not all AI health tools with regulatory authorization are clinically validated | Nature Medicine
Skip to main content Thank you for visiting nature.com. You are using a browser version with …

Internal medicine physicians are increasingly interacting with systems that implement
artificial intelligence (AI) and machine learning (ML) technologies. Some physicians and …

Public discourse about artificial intelligence (AI) and generative AI, in particular, is
ubiquitous. AI has been a focus of research in biomedical and health informatics since its …

Aims and objectives: To examine the nature and use of automation in contemporary clinical
information systems by reviewing studies reporting the implementation and evaluation of …

Objectives Surface the urgent dilemma that healthcare delivery organizations (HDOs) face
navigating the US Food and Drug Administration (FDA) final guidance on the use of clinical …

Machine learning (ML) solutions are increasingly entering healthcare. They are complex,
sociotechnical systems that include data inputs, ML models, technical infrastructure and …

Computerised decision support (CDS) tools enabled by artificial intelligence (AI) seek to
enhance accuracy and efficiency of clinician decision-making at the point of care. Statistical …

Digital Health to Patient-Facing Artificial Intelligence: Ethical Implications and Threats to Dignity
for Patients With Cancer | JCO Oncology Practice Skip to main content ASCO Publications …