Current societal challenges exceed the capacity of humans operating either alone or
collectively. As AI evolves, its role within human collectives will vary from an assistive tool to …

The rapid advancement of artificial intelligence (AI) is poised to reshape almost every line of
work. Despite enormous efforts devoted to understanding AI's economic impacts, we lack a …

We have reviewed the current literature focused on the role of artificial intelligence (AI) for
underserved populations and health equity in dermatology. Studies evaluating the utility and …

Diagnosing and treating skin diseases require advanced visual skills across multiple
domains and the ability to synthesize information from various imaging modalities. Current …

Vision-Language Models (VLMs) combine Large Language Model (LLM) capabilities with
image processing, enabling tasks like image captioning and text-to-image generation. Yet …

The recent increase in the prevalence of skin cancer, along with its significant impact on
individuals' lives, has garnered the attention of many researchers in the field of deep …

Multi-modal large language models (MLLMs) have been given free rein to explore exciting
medical applications with a primary focus on radiology report generation. Nevertheless, the …

In an era marked by exponential technological advancements, the convergence of
biosensors and artificial intelligence (AI) presents a transformative opportunity to …

The remarkable progress of deep learning in dermatological tasks has brought us closer to
achieving diagnostic accuracies comparable to those of human experts. However, while …

Deep learning has revolutionized cancer diagnostics, shifting from pixel-based image
analysis to more comprehensive, patient-centric care. This opinion article explores recent …