Prediction of Pulmonary Function Parameters Based on a Combination Algorithm

Prediction of Pulmonary Function Parameters Based on a Combination Algorithm

Objective: Pulmonary function parameters play a pivotal role in the assessment of respiratory diseases. However, the accuracy of the existing methods for the prediction of pulmonary function parameters is low. This study proposes a combination algorithm to improve the accuracy of pulmonary function...

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Bibliographic Details
Main Authors: Ruishi Zhou, Peng Wang, Yueqi Li, Xiuying Mou, Zhan Zhao, Xianxiang Chen, Lidong Du, Ting Yang, Qingyuan Zhan, Zhen Fang
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Bioengineering
Subjects:
combination algorithm
support vector machines
extreme gradient boosting
one-dimensional convolutional neural network
improved K-nearest neighbor
Online Access:https://www.mdpi.com/2306-5354/9/4/136

Internet

https://www.mdpi.com/2306-5354/9/4/136

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