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Titlebook: Computational Mathematics Modeling in Cancer Analysis; Second International Wenjian Qin,Nazar Zaki,Chao Li Conference proceedings 2023 The

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,MPSurv: End-to-End Multi-model Pseudo-Label Model for Brain Tumor Survival Prediction with Populatiset for the training and validation of segmentation and prediction tasks. Experimental results demonstrate that our model enhances the accuracy of brain tumor survival prediction and exhibits superior generalizability. The source code is available at: ..
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Shape-Aware Diffusion Model for Tumor Segmentation on Gd-EOB-DTPA MRI Images of Hepatocellular Carcfor effectively adapting to the variable characteristics of liver and tumor geometries, boundary shapes to achieve more accurate segmentation of HCC on Gd-EOB-DTPA MRI images. We conducted validation experiments on Gd-EOB-DTPA MRI images from 25 HCC patients, and the results demonstrated Dice and Io
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,Style Enhanced Domain Adaptation Neural Network for Cross-Modality Cervical Tumor Segmentation,to Domain Adversarial Neural Network (DANN)-based model to improve the generalization performance of the shared segmentation network. Experimental results show that our method achieves the best performance on the cross-modality cervical tumor segmentation task compared to current state-of-the-art UD
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Peter M. Winter,Leonard L. Firestoneevention was visually assessed by reviewing the excluded images after training. Three single institutional models (separately trained with single institutional data), a joint model (jointly trained using multi-institutional data), and two popular federated learning frameworks (FedAvg and FedProx) we
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Peter M. Winter,Leonard L. Firestoneaverage AUC was 0.74(0.69,0.76) and the accuracy was 0.73. It was followed by SVM, LR and KNN models, and the average AUC were 0.73(0.66,0.80), 0.71(0.62,0.78) and 0.66(0.61,0.72), respectively. The performance of stacking ensemble model showed effective improvement, with an average AUC of 0.77(0.67
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