Artificial intelligence (AI) in medicine and dermatology brings additional challenges related
to bias, transparency, ethics, security, and inequality. Bias in AI algorithms can arise from …

Skin lesions are essential for the early detection and management of a number of
dermatological disorders. Learning-based methods for skin lesion analysis have drawn …

Background The global use of artificial intelligence has the potential to revolutionize the
healthcare industry. Despite the fact that artificial intelligence is becoming more popular …

Digital twins, innovative virtual models synthesizing real-time biological, environmental, and
lifestyle data, herald a new era in personalized medicine, particularly dermatology. These …

Mobile health (mHealth) has recently had significant advances in tele-dermatology (TD)
thanks to the developments following the COVID-19 pandemic. This topic is very important …

Artificial intelligence (AI) is recently seeing significant advances in teledermatology (TD),
also thanks to the developments that have taken place during the COVID-19 pandemic. In …

As healthcare systems around the world face challenges such as escalating costs, limited
access, and growing demand for personalized care, artificial intelligence (AI) is emerging as …

Abstract Background and Objectives Artificial intelligence (AI) models trained on multi-
centric and multi-device studies can provide more robust insights and research findings …

Introduction The use of artificial intelligence (AI) as a diagnostic and decision-support tool is
increasing in dermatology. The accuracy of image-based AI tools is incumbent on images in …

The use of artificial intelligence as a medical device (AIaMD) in healthcare systems is
increasing rapidly. In dermatology, this has been accelerated in response to increasing skin …