An early aortic dissection screening model and applied research based on ensemble learning

BACKGROUND: As a particularly dangerous and rare cardiovascular disease, aortic dissection (AD) is characterized by complex and diverse symptoms and signs. In the early stage, the rate of misdiagnosis and missed diagnosis is relatively high. This study aimed to use machine learning technology to est...

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Detalles Bibliográficos
Autores principales: Liu, Lijue, Tan, Shiyang, Li, Yi, Luo, Jingmin, Zhang, Wei, Li, Shihao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7791246/
https://www.ncbi.nlm.nih.gov/pubmed/33437777
http://dx.doi.org/10.21037/atm-20-1475

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7791246/
https://www.ncbi.nlm.nih.gov/pubmed/33437777
http://dx.doi.org/10.21037/atm-20-1475

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