AI's good at diagnosing skin cancer

Conventionally, skin cancer's primarily diagnosed visually. It starts with a clinical screenings, then, if needed, followed by dermoscopic analyses, a biopsies and histopathological examinations. A team mainly from Stanford University, California, has reported in Nature that mHealth can provide an alternative. Classifying skin lesions using images is challenging, owing to fine-grained variabilities in their appearance. Convolutional Neural Networks (CNN) offer potential for dealing with fine-grained object categories. The team demonstrates skin lesion classifications using a single CNN, trained end-to-end directly from images using only pixels and disease labels as inputs.