Image-processing techniques in machine learning (ML) for skin cancer detection using clinical images.

A new dual-modal, non-invasive detection technique could make it easier—and faster—to differentiate between melanoma skin cancer and benign lesions.

The researchers suggest that these advanced, pretrained machine learning models could expand the reach of machine learning-based cancer diagnosis to resource-limited settings.

Researchers are using machine-learning to build tools in the realm of cancer detection and diagnosing, potentially catching tumors or lesions that doctors could miss.

A group of researchers at the University of Michigan developed a two-line strip test and micro-needle patch to detect melanoma from home.

Mount Sinai's Waldman Melanoma and Skin Cancer Center uses relatively new screening technology to detect and monitor spots.

LUGANO, 30 September, 2021 – A new study has found that a direct-to-consumer machine learning model for detecting skin cancers incorrectly classified rare and aggressive cancers as low-risk.1 ...

How your phone can help One of the best examples of new tech helping bridge this pandemic-fueled health care gap is the new skin-cancer-fighting app Miiskin (iOS, Android).