Researchers at the University of California San Diego School of Medicine have developed a new approach for identifying individuals with skin cancer that combines genetic ancestry, lifestyle and social ...

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 ...

The dual-modal technique combining OCT and Raman spectroscopy achieved 96.9% accuracy in differentiating melanoma from benign lesions. Early melanoma diagnosis is critical, with a 99% 5-year survival ...

Skin cancer is the most commonly diagnosed cancer in the United States, affecting one in five Americans during their lifetime. While basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs) ...

Raman spectroscopy, paired with AI, offers a non-invasive method for detecting skin cancer, showing good diagnostic accuracy. Regulatory challenges and machine bulkiness limit the clinical adoption of ...

A team of researchers from the University of Chicago's Pritzker School of Molecular Engineering (UChicago PME) has used Quantum Machine Learning (QML) to identify cancer early.

Overview: AI is transforming medical diagnosis by allowing earlier and more accurate disease detection.Machine learning ...

According to the American Cancer Society, more than 100,000 people will be diagnosed with melanoma this year. The good news is now that treatments have advanced, death rates have declined. Diagnostic ...

Cancer diagnoses traditionally require invasive or labor-intensive procedures such as tissue biopsies. Researchers at the Ludwig-Maximilians-Universität München (LMU) have now reported on a method ...