New data from the MEL-SELF trial show gaps in melanoma self-surveillance confidence, highlighting opportunities to improve ...

In a recent review published in the Life Journal, a group of authors reviewed image-processing techniques in machine learning (ML) for skin cancer detection using clinical images, evaluating their ...

Researchers at Fox Chase Cancer Center, Temple University's College of Engineering, and the Lewis Katz School of Medicine at Temple University have developed a new method that enhances the ability of ...

Melanoma remains one of the hardest skin cancers to diagnose because it often mimics harmless moles or lesions. While most artificial intelligence (AI) tools rely on dermoscopic images alone, they ...

Across various classes, the researchers identified a model that, when coupled with appropriate data augmentation and optimization partner, may help aid in the detection of skin cancer. Using an ...