Translational bioethics expands the scope of research ethics to include multidisciplinary
analyses of the societal implications of new translational science discoveries. Novel health …

The research ethics framework put forward by McCradden et al.(2022) to support systematic
inquiry in the development of artificial intelligence (AI) and machine learning (ML) …

The application of machine learning (ML) in health care holds great promise for improving
care. Indeed, our own team is collaborating with experts in machine learning and statistical …

The ethical integration of Artificial Intelligence (AI) in healthcare necessitates addressing
fairness-a concept that is highly context-specific across medical fields. Extensive studies …

Background Hepatocellular carcinoma (HCC) represents a considerable burden to patients
and health systems. Microvascular invasion (MVI) is a significant risk factor for HCC …

The ethics of artificial intelligence (AI) and machine learning (ML) exemplify the conceptual
struggle between applying familiar pathways of ethical analysis versus generating novel …

Intrusion detection, a pivotal facet of securing digital environments, intersects with the
proliferation of machine learning (ML) technologies, which have driven transformative …

A novel advantage of the use of machine learning (ML) systems in medicine is their potential
to continue learning from new data after implementation in clinical practice. To date …

Medical applications of machine learning (ML) have shown promise in analyzing patient
data to support clinical decision-making and provide patient-specific outcomes. In …

McCradden et al.'s (2022) article makes a distinctive contribution to the growing literature on
the ethics of artificial intelligence in medicine. Not only do the authors raise important ethical …