Fig. 1: Design and flowchart of the deep learning framework.
From: Deep learning models in classifying primary bone tumors and bone infections based on radiographs
a Preprocessing of data. The input of the models mainly includes image information based on radiographs defined as input (A) and clinical information defined as input (B). b Model development. c Comprehensive prediction. PRadio and PClinic refers to the results of the four imaging models (E3, E4, ViT, and SWIN) and the clinic model, respectively. d Evaluation. This part is mainly composed of ROC curve and confusion matrix. e Verifying. The results of models are compared with radiologists with different seniority. n number of the radiographs, E3 EfficientNet B3, E4 EfficientNet B4, ViT vision transformer, SWIN swin transformers. Note: Fig. 1 was Created with BioRender.com.
