Risk factors based vessel‐specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry

BACKGROUND AND HYPOTHESIS: The recently introduced Bayesian quantile regression (BQR) machine‐learning method enables comprehensive analyzing the relationship among complex clinical variables. We analyzed the relationship between multiple cardiovascular (CV) risk factors and different stages of coro...

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Detalles Bibliográficos
Autores principales: Park, Hyung‐Bok, Lee, Jina, Hong, Yongtaek, Byungchang, So, Kim, Wonse, Lee, Byoung K., Lin, Fay Y., Hadamitzky, Martin, Kim, Yong‐Jin, Conte, Edoardo, Andreini, Daniele, Pontone, Gianluca, Budoff, Matthew J., Gottlieb, Ilan, Chun, Eun Ju, Cademartiri, Filippo, Maffei, Erica, Marques, Hugo, Gonçalves, Pedro de A., Leipsic, Jonathon A., Shin, Sanghoon, Choi, Jung H., Virmani, Renu, Samady, Habib, Chinnaiyan, Kavitha, Stone, Peter H., Berman, Daniel S., Narula, Jagat, Shaw, Leslee J., Bax, Jeroen J., Min, James K., Kook, Woong, Chang, Hyuk‐Jae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Clinical Trial
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018106/
https://www.ncbi.nlm.nih.gov/pubmed/36691990
http://dx.doi.org/10.1002/clc.23964

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018106/
https://www.ncbi.nlm.nih.gov/pubmed/36691990
http://dx.doi.org/10.1002/clc.23964

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