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SHAP Model Explainability in ECMO – PAL mortality prediction: A Critical Analysis. Author’s reply

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Fig. 1

Data availability

Data is available by direct request to the Extracorporeal Life Support Organization (ELSO.org).

References

  1. Stephens AF, Šeman M, Diehl A et al (2023) ECMO PAL: using deep neural networks for survival prediction in venoarterial extracorporeal membrane oxygenation [published online ahead of print, 2023 Aug 7]. Intensive Care Med. https://doi.org/10.1007/s00134-023-07157-x

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  2. Fernández MV, de Aledo ALG, Moya FPD. SHAP Model Explainability in ECMO – PAL mortality prediction: A Critical Analysis. Intensive Care Med. https://doi.org/10.1007/s00134-023-07252-z

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Funding

Funding was provided by the National Health and Medical Research Council (CRE-ICU).

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Authors and Affiliations

  1. Cardio-Respiratory Engineering and Technology Laboratory, Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, AU, USA

    Andrew F. Stephens, Michael Šeman & Shaun D. Gregory

  2. School of Public Health and Preventive Medicine, Monash University, Melbourne, AU, USA

    Carol L. Hodgson

Authors
  1. Andrew F. Stephens
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  2. Michael Šeman
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  3. Carol L. Hodgson
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  4. Shaun D. Gregory
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Correspondence to Andrew F. Stephens.

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This comment refers to the article available online at https://doi.org/10.1007/s00134-023-07157-x.

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Stephens, A.F., Šeman, M., Hodgson, C.L. et al. SHAP Model Explainability in ECMO – PAL mortality prediction: A Critical Analysis. Author’s reply. Intensive Care Med 49, 1560–1562 (2023). https://doi.org/10.1007/s00134-023-07237-y

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  • DOI: https://doi.org/10.1007/s00134-023-07237-y

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