Melanoma is the deadliest form of skin cancer and can be challenging to diagnose. In order to improve the rate at which treatment can be accessed, detection and diagnosis rates must also improve. The volume of skin biopsies continues to rise amid a declining pathologist population, slowing the rate of diagnosis and therefore, treatment. Earlier this month, Proscia released study data in which artificial intelligence (AI) was used to detect melanoma with a high degree of accuracy. To find out more about how AI can improve melanoma diagnosis, Technology Networks spoke to Dr. Kiran Motaparthi, director of dermatopathology and clinical associate professor of dermatology at the University of Florida and Julianna Ianni, PhD, vice president of AI R&D, Proscia.

Melanoma is a type of skin cancer that begins in cells known as melanocytes. The cancer is so dangerous because of its ability to spread to other organs more rapidly if it is not treated early. It is so deadly that cancer is responsible for 70 percent of all skin cancer-related deaths worldwide. Usually, physicians use visual inspection tools to detect suspicious pigmented lesions (SPLs), indicating skin cancer. Early identification of SPL can improve melanoma prognosis and significantly reduce treatment costs.

As an internist, Dr. Joann Elmore was taught to ask questions. Those questions led her to spend much of her career in breast cancer research where she found extensive variability among radiologists' interpretation of mammograms. "Radiology data is subjective, just like art. You're being asked to classify visual data," Elmore says. It wasn't until she was on the receiving end of a Friday night phone call alerting her to a "suspicious" skin biopsy, however, did Elmore's interest in melanoma peak.