Classification of pain expression images in elderly with hip fractures based on improved ResNet50 network - Shuang, Yang; Liangbo, Gong; Huiwen, Zhao; Jing, Liu; Xiaoying, Chen; Siyi, Shen; Xiaoya, Zhu; Wen, Luo (Frontiers in Medicine, 2024)
The aim of this study is designed a improved ResNet50 network to achieve automatic classification model for pain expressions by elderly patients with hip fractures. This study built a dataset by combining the advantages of deep learning in image recognition, using a hybrid of the Multi-Task Cascaded Convolutional Neural Networks (MTCNN). Based on ResNet50 network framework utilized transfer learning to implement model function. This study performed the hyperparameters by Bayesian optimization in the learning process. This study calculated intraclass correlation between visual analog scale scores provided by clinicians independently and those provided by pain expression evaluation assistant(PEEA).The automatic pain expression recognition model in elderly patients with hip fractures,