Emerging machine learning (ML) technologies have the potential to significantly improve the
research and treatment of rare diseases, which constitute a vast set of diseases that affect a …

It is critical that diet quality be assessed and discussed at the point of care with clinicians
and other members of the healthcare team to reduce the incidence and improve the …

Background Rare disease diagnosis is often delayed by years. A primary factor for this delay
is a lack of knowledge and awareness regarding rare diseases. Probabilistic diagnostic …

Diagnostic error may be the largest unaddressed patient safety concern in the United States,
responsible for an estimated 40,000–80,000 deaths annually. With the electronic health …

Abstract Clinical Decision Support Systems (CDSSs) are used in a clinical setting to help
physicians make decisions to improve clinical performance and patient care. There are …

Background Well-established electronic data capture in UK general practice means that
algorithms, developed on patient data, can be used for automated clinical decision support …

Objectives To identify the barriers and facilitators to the successful implementation of
imaging-based diagnostic artificial intelligence (AI)-assisted decision-making software in …

Rationale & Objective Most adults with chronic kidney disease (CKD) in the United States
are cared for by primary care providers (PCPs). We evaluated the feasibility and preliminary …

Background Venous thromboembolism has been a major public health problem and caused
a heavy disease burden. Venous thromboembolism clinical decision support system was …

Rory Staunton, a 12 year-old boy, presented with fever, vomiting and mottled skin. Was this
gastroenteritis? Thomas Duncan's symptoms were headache, dizziness, nausea, abdominal …