Calibration drift in regression and machine learning models for acute kidney injury

Sharon E. Davis; Thomas A. Lasko; Guanhua Chen; Edward D. Siew; Michael E. Matheny

doi:10.1093/jamia/ocx030

March 13, 2017Journal of the American Medical Informatics AssociationOpen Access

Calibration drift in regression and machine learning models for acute kidney injury

View Full Paper

Ask AI

Bookmark

Share

Key Points

The aim is to outline the necessity of efficient model updating protocols to maintain prediction accuracy in acute kidney injury.
Identified variations in calibration drift across different methods.
Proposed protocols for updating models during rapid performance changes.
Emphasized the importance of tailored updating frequencies rather than fixed intervals.
Highlight that regular intervals for model updates are insufficient.
Show that models need updates during performance drift for accurate predictions.
Emphasize the need for personalized and responsive updating strategies.

Implication

Demonstrates essential updating protocols for accurate risk predictions in acute kidney injury, suggesting tailored approaches for model maintenance.

Abstract

Efficient and effective updating protocols will be essential for maintaining accuracy of, user confidence in, and safety of personalized risk predictions to support decision-making. Model updating protocols should be tailored to account for variations in calibration drift across methods and respond to periods of rapid performance drift rather than be limited to regularly scheduled annual or biannual intervals.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Davis et al. (2017) studied this question.

synapsesocial.com/papers/69d967651ad561c67368407e https://doi.org/10.1093/jamia/ocx030

View Full Paper

Ask AI

Bookmark

Share

Calibration drift in regression and machine learning models for acute kidney injury

Key Points

Implication

Abstract

Discussion

Cite This Study

Calibration drift in regression and machine learning models for acute kidney injury

Key Points

Implication

Abstract

Discussion

Cite This Study

Keep reading

Keep reading