Nov 30, 2023 · This study proposes a unique data augmentation method to improve the model robustness and the corresponding response capacity under extreme respiratory ...

May 15, 2024 · This study proposes a unique data augmentation method to improve the model robustness and the corresponding response capacity under extreme respiratory ...

A High-Dimensional Respiratory Motion Modeling Method Based on Machine Learning ... motion model using a weighted sparse algorithm and motion prior-based ...

A solution is to develop a respiratory motion model. The aim of this study is to construct a respiratory motion model that can accommodate extreme respiratory ...

A high-dimensional respiratory motion modeling method based on machine learning ... Authors: Zeyang Zhou; Shan Jiang; Zhiyong Yang; Ning Zhou; Shixing Ma; Yuhua ...

This study proposes a unique data augmentation method to improve the model robustness and the corresponding response capacity under extreme respiratory ...

本研究的目的是构建一个可以适应极端呼吸条件的呼吸运动模型。采用主成分分析（PCA）和支持向量回归（SVR）方法作为框架来构建呼吸运动模型。在第一阶段，提取内部呼吸信号 ...

Jan 5, 2024 · In this paper, we propose a novel deep learning architecture for respiratory motion prediction, which can adapt to different patients.

Jun 14, 2016 · We have proposed a prediction framework for high-dimensional states subject to respiratory motion. The learning approach is particularly ...

This study demonstrates the potential of deep LSTM models for the respiratory signal prediction and illustrates the impacts of major hyper-parameters in LSTM ...