Published on in Vol 5 (2024)

This is a member publication of University of Bristol (Jisc)

Preprints (earlier versions) of this paper are available at https://www.medrxiv.org/content/10.1101/2023.01.21.23284795v1, first published .
Performance Drift in Machine Learning Models for Cardiac Surgery Risk Prediction: Retrospective Analysis

Performance Drift in Machine Learning Models for Cardiac Surgery Risk Prediction: Retrospective Analysis

Performance Drift in Machine Learning Models for Cardiac Surgery Risk Prediction: Retrospective Analysis

Tim Dong   1 , MSc ;   Shubhra Sinha   1 , MBBS ;   Ben Zhai   2 , PhD ;   Daniel Fudulu   1 , MD, PhD ;   Jeremy Chan   1 , MD ;   Pradeep Narayan   3 , MD ;   Andy Judge   1 , PhD ;   Massimo Caputo   1 , MD ;   Arnaldo Dimagli   1 , MD ;   Umberto Benedetto   1 , MD, PhD ;   Gianni D Angelini   1 , MD

1 Bristol Heart Institute, Translational Health Sciences, University of Bristol, Bristol, United Kingdom

2 School of Computing Science, Northumbria University, Newcastle upon Tyne, United Kingdom

3 Department of Cardiac Surgery, Rabindranath Tagore International Institute of Cardiac Sciences, West Bengal, India

Corresponding Author:

  • Tim Dong, MSc
  • Bristol Heart Institute
  • Translational Health Sciences
  • University of Bristol
  • Terrell St
  • Bristol, BS2 8ED
  • United Kingdom
  • Phone: 44 75 6416 8791
  • Email: qd18830@bristol.ac.uk