Development and utility assessment of a machine learning bloodstream infection classifier in pediatric patients receiving cancer treatments
Abstract Background Objectives were to build a machine learning algorithm to identify bloodstream infection (BSI) among pediatric patients with cancer and hematopoietic stem cell transplantation (HSCT) recipients, and to compare this approach with presence of neutropenia to identify BSI. Methods We...
Main Authors: | Lillian Sung, Conor Corbin, Ethan Steinberg, Emily Vettese, Aaron Campigotto, Loreto Lecce, George A. Tomlinson, Nigam Shah |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2020-11-01
|
Series: | BMC Cancer |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12885-020-07618-2 |
Similar Items
-
Clinical Characteristics And Risk Factors In Mixed-Enterococcal Bloodstream Infections
by: Zheng C, et al.
Published: (2019-10-01) -
Management of enterococcal central line-associated bloodstream infections in patients with cancer
by: Hesham Awadh, et al.
Published: (2021-07-01) -
Risk factors for nosocomial bloodstream infection caused by multidrug resistant gram-negative bacilli in pediatrics
by: Mariana V. Arnoni, et al. -
Central line-associated bloodstream infection in pediatric oncology patients in Qatar: A prospective study
by: Tayseer Alsaad, et al.
Published: (2017-01-01) -
Epidemiology of Bloodstream Infections at a Cancer Center
by: Eduardo Velasco, et al.
Published: (2000-09-01)