A boosting inspired personalized threshold method for sepsis screening

DOI10.1080/02664763.2020.1716695OpenAlexW3002551147WikidataQ126293006 ScholiaQ126293006MaRDI QIDQ5861518

No author found.

Publication date: 1 March 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8188988

zbMATH Keywords

screeningboostingsepsisclinical risk scorepersonalized thresholds

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• AdaBoost.MH
• AdaBoost-SAMME

Cites Work

• Unnamed Item
• Multi-class AdaBoost
• A decision-theoretic generalization of on-line learning and an application to boosting
• Defining an optimal cut-point value in ROC analysis: an alternative approach
• Boosting with early stopping: convergence and consistency
• On early stopping in gradient descent learning
• Maximally Selected Chi Square Statistics
• The elements of statistical learning. Data mining, inference, and prediction
• Logistic regression, AdaBoost and Bregman distances

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