Comparative Study on the Application of Deep Learning Algorithm in Burn Depth Diagnosis

As one of the main causes of casualties in the world, fires, burns and scalds result in serious social and economic burdens in the world, and the annual incidence of burns in China exceeds 1%. However, the accuracy of surgeons in judging burn depth is quite low at present, with less than 50% accuracy of inexperienced doctors and only 64% to 76% accuracy of experienced doctors. For these reasons, there is great potential according to the studies on burn diagnosis based on deep learning algorithm. Therefore, in this study, a variety of convolutional neural networks were used to compare the classification of burn degree, and the processed datasets were used for training. By testing a series of neural networks, the best result was the precision of 88.75% when using the pre-trained VGG16 network. This result shows that the deep learning algorithm has high accuracy and application potential in the field of burn diagnosis.