Closing the Gap in Surveillance and Audit of Invasive Mold Diseases for Antifungal Stewardship Using Machine Learning

Clinical audit of invasive mold disease (IMD) in hematology patients is inefficient due to the difficulties of case finding. This results in antifungal stewardship (AFS) programs preferentially reporting drug cost and consumption rather than measures that actually reflect quality of care. We used ma...

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Detalles Bibliográficos
Autores principales: Baggio, Diva, Peel, Trisha, Peleg, Anton Y., Avery, Sharon, Prayaga, Madhurima, Foo, Michelle, Haffari, Gholamreza, Liu, Ming, Bergmeir, Christoph, Ananda-Rajah, Michelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6780614/
https://www.ncbi.nlm.nih.gov/pubmed/31491944
http://dx.doi.org/10.3390/jcm8091390

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6780614/
https://www.ncbi.nlm.nih.gov/pubmed/31491944
http://dx.doi.org/10.3390/jcm8091390

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