首页|First Affiliated Hospital of Gannan Medical University Reports Findings in Thymo ma (Application of machine learning for the differentiation of thymomas and thym ic cysts using deep transfer learning: A multi-center comparison of diagnostic . ..)
First Affiliated Hospital of Gannan Medical University Reports Findings in Thymo ma (Application of machine learning for the differentiation of thymomas and thym ic cysts using deep transfer learning: A multi-center comparison of diagnostic . ..)
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New research on Lymphatic Diseases and Conditions -Thymoma is the subject of a report. According to news originating from Ganzhou, People's Republic of China, by NewsRx correspondents, research sta ted, "This study aimed to evaluate the feasibility and performance of deep trans fer learning (DTL) networks with different types and dimensions in differentiati ng thymomas from thymic cysts in a retrospective cohort. Based on chest-enhanced computed tomography (CT), the region of interest was delineated, and the maximu m cross section of the lesion was selected as the input image." Our news journalists obtained a quote from the research from the First Affiliate d Hospital of Gannan Medical University, "Five convolutional neural networks (CN Ns) and Vision Transformer (ViT) were used to construct a 2D DTL model. The 2D m odel constructed by the maximum section (n) and the upper and lower layers (n -1, n + 1) of the lesion was used for feature extraction, and the features were s elected. The remaining features were pre-fused to construct a 2.5D model. The wh ole lesion image was selected for input and constructing a 3D model. In the 2D m odel, the area under curve (AUC) of Resnet50 was 0.950 in the training cohort an d 0.907 in the internal validation cohort. In the 2.5D model, the AUCs of Vgg11 in the internal validation cohort and external validation cohort 1 were 0.937 an d 0.965, respectively. The AUCs of Inception_v3 in the training coh ort and external validation cohort 2 were 0.981 and 0.950, respectively. The AUC values of 3D_Resnet50 in the four cohorts were 0.987, 0.937, 0.938 , and 0.905."
GanzhouPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesHealth and MedicineLymphatic Diseases and C onditionsMachine LearningThymomaThymus Neoplasms
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