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Currently submitted to: JMIRx Med

Date Submitted: May 9, 2024
Date Accepted: May 9, 2024

The final, peer-reviewed published version of this preprint can be found here:

Authors’ Response to Peer Reviews of “Performance Drift in Machine Learning Models for Cardiac Surgery Risk Prediction: Retrospective Analysis”

Dong T, Sinha S, Zhai B, Fudulu D, Chan J, Narayan P, Judge A, Caputo M, Dimagli A, Benedetto U, Angelini G

Authors’ Response to Peer Reviews of “Performance Drift in Machine Learning Models for Cardiac Surgery Risk Prediction: Retrospective Analysis”

JMIRx Med 2024;5:e60384

DOI: 10.2196/60384

PMCID: 11217161

Author(s)’ Responses to Peer Review Reports

  • Tim Dong; 
  • Shubhra Sinha; 
  • Ben Zhai; 
  • Daniel Fudulu; 
  • Jeremy Chan; 
  • Pradeep Narayan; 
  • Andy Judge; 
  • Massimo Caputo; 
  • Arnaldo Dimagli; 
  • Umberto Benedetto; 
  • Gianni Angelini

ABSTRACT

This is the author(s)’ responses to peer review reports related to MS ID45973.


 Citation

Please cite as:

Dong T, Sinha S, Zhai B, Fudulu D, Chan J, Narayan P, Judge A, Caputo M, Dimagli A, Benedetto U, Angelini G

Authors’ Response to Peer Reviews of “Performance Drift in Machine Learning Models for Cardiac Surgery Risk Prediction: Retrospective Analysis”

JMIRx Med 2024;5:e60384

DOI: 10.2196/60384

PMCID: 11217161

Per the author's request the PDF is not available.

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