Predicting Orthopedic Surgery Types Using Convolutional Neural Networks

Abstract

In recent years, cost control has been an important issue in hospitals. The results of cost control will directly affect the profits and sustainable development of hospitals. In the operating room, the cost of the operating room is affected by the surgical schedule. A suitable surgical schedule will depend on whether the duration and type of surgery can be accurately predicted. Therefore, in this study, a convolutional neural networks model was proposed to predict the orthopedic surgical type by X-ray images. Based on the experimental data, the proposed model can accurately predict the type of orthopedic surgery. In addition, the prediction accuracy of the model is significantly influenced by the hyper-parameters of the model. In future research, it is recommended to use metaheuristic algorithms to find more suitable combinations of hyper-parameters.

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