Paper
28 August 2023 Research on children's respiratory diseases based on partition level multi-view clustering
Hongying Zhang, Yaxiong Wan, Kaiwu Zhang
Author Affiliations +
Proceedings Volume 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023); 127242A (2023) https://doi.org/10.1117/12.2687644
Event: Second International Conference on Biomedical and Intelligent Systems (IC-BIS2023), 2023, Xiamen, China
Abstract
Respiratory tract infection is a major disease that affects children's physical development and physical and mental health. Vitamin D intake has a certain internal relationship and correlation with the incidence of respiratory tract diseases. We selected children with respiratory tract infection as the research data to study the correlation between vitamin D intake and respiratory tract infection in children. In order to better analyze data information, multi-view clustering as an important unsupervised learning method is applied to the above research. In this paper, we propose a novel partition-level multi-view clustering method with weighted adaptive graph learning, which not only captures global and local structures simultaneously, but also fuses multi-view information through a weighted fusion mechanism. The effectiveness of our proposed method was verified on three public datasets, and the method was applied to respiratory disease datasets to achieve good clustering results.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongying Zhang, Yaxiong Wan, and Kaiwu Zhang "Research on children's respiratory diseases based on partition level multi-view clustering", Proc. SPIE 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023), 127242A (28 August 2023); https://doi.org/10.1117/12.2687644
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KEYWORDS
Matrices

Pulmonary disorders

Data modeling

Shrinkage

Data fusion

Eigenvectors

Information technology

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