Cargando…
Use of machine learning models to predict prognosis of combined pulmonary fibrosis and emphysema in a Chinese population
BACKGROUND: Combined pulmonary fibrosis and emphysema (CPFE) is a novel clinical entity with a poor prognosis. This study aimed to develop a clinical nomogram model to predict the 1-, 2- and 3-year mortality of patients with CPFE by using the machine learning approach, and to validate the predictive...
Autores principales: | Liu, Qing, Sun, Di, Wang, Yu, Li, Pengfei, Jiang, Tianci, Dai, Lingling, Duo, Mengjie, Wu, Ruhao, Cheng, Zhe |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9422147/ https://www.ncbi.nlm.nih.gov/pubmed/36038872 http://dx.doi.org/10.1186/s12890-022-02124-6 |
Ejemplares similares
-
Prognosis of combined pulmonary fibrosis and emphysema: comparison
with idiopathic pulmonary fibrosis alone
por: Jiang, Chun-guo, et al.
Publicado: (2019) -
Construction of a diagnostic signature and immune landscape of pulmonary arterial hypertension
por: Duo, Mengjie, et al.
Publicado: (2022) -
Bioinformatic analysis and preliminary validation of potential therapeutic targets for COVID-19 infection in asthma patients
por: Li, Yue, et al.
Publicado: (2022) -
Mortality in combined pulmonary fibrosis and emphysema patients is determined by the sum of pulmonary fibrosis and emphysema
por: Zhao, An, et al.
Publicado: (2021) -
Impact and prognosis of lung cancer in patients with combined pulmonary fibrosis and emphysema
por: Oh, Jee Youn, et al.
Publicado: (2020)