Re-Defining High Risk COPD with Parameter Response Mapping Based on Machine Learning Models

PURPOSE: To explore optimal threshold of FEV1% predicted value (FEV1%pre) for high-risk chronic obstructive pulmonary disease (COPD) using the parameter response mapping (PRM) based on machine learning classification model. PATIENTS AND METHODS: A total of 561 consecutive non-COPD subjects who were...

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Detalles Bibliográficos
Autores principales: Pu, Yu, Zhou, Xiuxiu, Zhang, Di, Guan, Yu, Xia, Yi, Tu, Wenting, Lu, Yang, Zhang, Weidong, Fu, Chi-Cheng, Fang, Qu, de Bock, Geertruida H, Liu, Shiyuan, Fan, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9547550/
https://www.ncbi.nlm.nih.gov/pubmed/36217330
http://dx.doi.org/10.2147/COPD.S369904

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9547550/
https://www.ncbi.nlm.nih.gov/pubmed/36217330
http://dx.doi.org/10.2147/COPD.S369904

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