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Development and Validation of a Machine Learning Model to Estimate Bacterial Sepsis Among Immunocompromised Recipients of Stem Cell Transplant
IMPORTANCE: Sepsis disproportionately affects recipients of allogeneic hematopoietic cell transplant (allo-HCT), and timely detection is crucial. However, the atypical presentation of sepsis within this population makes detection challenging, and existing clinical sepsis tools have limited prognosti...
Autores principales: | Lind, Margaret L., Mooney, Stephen J., Carone, Marco, Althouse, Benjamin M., Liu, Catherine, Evans, Laura E., Patel, Kevin, Vo, Phuong T., Pergam, Steven A., Phipps, Amanda I. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Association
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056279/ https://www.ncbi.nlm.nih.gov/pubmed/33871619 http://dx.doi.org/10.1001/jamanetworkopen.2021.4514 |
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