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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...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
AME Publishing Company
2020
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| Materias: | |
| 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 |