We investigated whether human preferences hold the potential to improve diagnostic
artificial intelligence (AI)-based decision support using skin cancer diagnosis as a use case …

The rapid increase in telemedicine coupled with recent advances in diagnostic artificial
intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI …

Background Previous studies of artificial intelligence (AI) applied to dermatology have
shown AI to have higher diagnostic classification accuracy than expert dermatologists; …

The presence of dermatological information on social media has grown exponentially over
the last two decades. Consequently, the recent literature on this topic is abundant. Many …

Teaching methods in medical education have been changing. More recent teaching
modalities have gone beyond the traditional delivery of knowledge, promoting learning …

Background and objectives Convolutional neural networks (CNN) enable accurate
diagnosis of medical images and perform on or above the level of individual physicians …

BACKGROUND Microvascular tissue reconstruction is a well-established, commonly used
technique for a wide variety of the tissue defects. However, flap failure is associated with an …

Artificial Intelligence (AI) is increasingly being used in education, but mostly to support
individual teaching and learning. However, there are good reasons to think that thinking …

Background Preoperative assessment of whether a melanoma is invasive or in situ (MIS) is
a common task that might have important implications for triage, prognosis and the selection …

Zusammenfassung Hintergrund und Ziele Faltende neuronale Netzwerke (CNN)
ermöglichen eine exakte Diagnose medizinischer Bilder und erzielen eine vergleichbare …