Importance Clinical artificial intelligence (AI) algorithms have the potential to improve clinical
care, but fair, generalizable algorithms depend on the clinical data on which they are trained …

An estimated 3 billion people lack access to dermatological care globally. Artificial
intelligence (AI) may aid in triaging skin diseases and identifying malignancies. However …

Artificial intelligence is poised to rapidly reshape many fields, including that of skin cancer
screening and diagnosis, both as a disruptive and assistive technology. Together with the …

The inferences of most machine-learning models powering medical artificial intelligence are
difficult to interpret. Here we report a general framework for model auditing that combines …

While artificial intelligence (AI) holds promise for supporting healthcare providers and
improving the accuracy of medical diagnoses, a lack of transparency in the composition of …

Images depicting dark skin tones are significantly underrepresented in the educational
materials used to teach primary care physicians and dermatologists to recognize skin …

There is a scarcity of nursing literature, studies, and educational materials on the
assessment and early recognition of both common and serious integumentary and general …

Despite the proliferation and clinical deployment of artificial intelligence (AI)-based medical
software devices, most remain black boxes that are uninterpretable to key stakeholders …

Recent advances in artificial intelligence research have led to an increase in the
development of algorithms for detecting malignancies from clinical and dermoscopic images …

Featured Application The research results provide guidelines for the lighting of photographic
scenes where accurate colour reproduction is important. Abstract In both commercial and …