Machine learning-based combined nomogram for predicting the risk of pulmonary invasive fungal infection in severely immunocompromised patients

BACKGROUND: Early and accurate diagnosis of invasive fungal infection (IFI) is pivotal for the initiation of effective antifungal therapy for patients with hematologic malignancies. METHODS: This retrospective study involved 235 patients with hematologic malignancies and pulmonary infections diagnos...

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Detalles Bibliográficos
Autores principales: Yan, Chenggong, Hao, Peng, Wu, Guangyao, Lin, Jie, Xu, Jun, Zhang, Tianjing, Li, Xiangying, Li, Haixia, Wang, Sibin, Xu, Yikai, Woodruff, Henry C., Lambin, Philippe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9347049/
https://www.ncbi.nlm.nih.gov/pubmed/35928747
http://dx.doi.org/10.21037/atm-21-4980

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9347049/
https://www.ncbi.nlm.nih.gov/pubmed/35928747
http://dx.doi.org/10.21037/atm-21-4980

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