Prediction of in-hospital adverse clinical outcomes in patients with pulmonary thromboembolism, machine learning based models

BACKGROUND: Pulmonary thromboembolism (PE) is the third leading cause of cardiovascular events. The conventional modeling methods and severity risk scores lack multiple laboratories, paraclinical and imaging data. Data science and machine learning (ML) based prediction models may help better predict...

Descripción completa

Detalles Bibliográficos
Autores principales: Jenab, Yaser, Hosseini, Kaveh, Esmaeili, Zahra, Tofighi, Saeed, Ariannejad, Hamid, Sotoudeh, Houman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Cardiovascular Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043172/
https://www.ncbi.nlm.nih.gov/pubmed/36998977
http://dx.doi.org/10.3389/fcvm.2023.1087702

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043172/
https://www.ncbi.nlm.nih.gov/pubmed/36998977
http://dx.doi.org/10.3389/fcvm.2023.1087702

Ejemplares similares