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An efficient machine learning framework to identify important clinical features associated with pulmonary embolism
A misdiagnosis of pulmonary embolism (PE) can have severe consequences such as disability or death. It’s crucial to accurately identify key clinical features of PE in clinical practice to promptly identify potential PE patients who may present asymptomatically, and to prevent misdiagnosing PE as ast...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10538737/ https://www.ncbi.nlm.nih.gov/pubmed/37768933 http://dx.doi.org/10.1371/journal.pone.0292185 |