Skin cancer remains the most common form of cancer worldwide, often presenting as benign skin conditions that are difficult to differentiate, even for experienced dermatologists. Misdiagnosis can lead ...

Scientists developed a way of using artificial intelligence to check for skin cancer with the AI tool, which was trained on data from 53,601 skin lesions from 25,105 patients, outperforming existing ...

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 ...

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 ...

A new deep learning system developed by an international research team detects melanoma with 94.5% accuracy by fusing dermoscopic images and patient metadata such as age, gender, and lesion location.

A future where artificial intelligence will guide skin cancer detection is in sight, experts say, even as human care remains essential. “The whole ecosystem has really matured and we are now past the ...

The implementation of a modified Skin and Ultraviolet Neoplasia Transplant Risk Assessment Calculator (SUNTRAC) risk-based surveillance program, which included primary care, dermatology, and ...

Please provide your email address to receive an email when new articles are posted on . Solid organ transplant recipients are 7.8 times more likely to develop skin cancer. Risk-stratified surveillance ...

Led by Aliyu Tetengi Ibrahim and his team at Ahmadu Bello University, a study published in Data Science and Management on November 2, 2024, introduces an innovative AI model that could revolutionize ...