Frostbite Detection: A Convolutional Neural Network Approach for Automatic Frostbite Detection

Frostbite is a term used to describe injury caused by exposure to extreme temperatures. It is often associated with outdoor activities, outdoor activities, and leisure activities in winter. However, frostbite may also occur in people undergoing cryotherapy, dermatology, hair therapy, sports medicine, and military service. Skin frostbite can range from mild to severe and can cause skin necrosis or cuts. The severity of frostbite depends on many factors, including temperature, humidity, and exposure time. Traditionally, the diagnosis of frostbite relied on the doctor's assessment, leading to inconsistencies. The seasonality and incidence of frostbite further complicate early recognition and diagnosis of frostbite, especially for first responders or laypersons, especially in the event of an emergency. Deep learning techniques, especially CNNs, hold great promise for improving frostbite diagnosis and assessment. CNNs have proven useful in the field of medicine and skin diseases. This study aims to develop and validate a CNN-based method to diagnose and analyze frostbite skin to provide clinicians with a more objective and effective diagnostic tool.