Background Artificial intelligence (AI) is increasingly being used in patient care. In the future,
physicians will need to understand not only the basic functioning of AI applications, but also …

Although numerous ethical principles and guidelines have been proposed to guide the
development of artificial intelligence (AI) systems, it has proven difficult to translate these …

The success of artificial intelligence depends on whether it can penetrate the boundaries of
evidence-based medicine, the lack of policies, and the resistance of medical professionals …

Background The reporting of machine learning (ML) prognostic and diagnostic modeling
studies is often inadequate, making it difficult to understand and replicate such studies. To …

To the Editor—The promise of machine learning (ML) to augment medical decision-making
in dynamic care environments has yet to be fully realized because of a gap in how …

With the advancement of computer technology, machine learning-based artificial
intelligence technology has been increasingly integrated and applied in the fields of …

Aim Sepsis is a leading cause of morbidity and mortality in neonates. Early diagnosis is key
but difficult due to non‐specific signs. We investigate the predictive value of machine …

Introduction The increasing availability of data and computing power has made machine
learning (ML) a viable approach to faster, more efficient healthcare delivery. Methods A …

The degree to which artificial intelligence healthcare research is informed by data and
stakeholders from community settings has not been previously described. As communities …

Abstract Background Despite global popularity, Community-based Health Intervention
(CBHI) programmes have yet to be fully incorporated into Singapore's public healthcare …