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Building a better machine learning model of extubation for neurocritical care patients. Author’s reply

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The Original Article was published on 05 November 2022

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References

  1. Ono S (2022) Building a better machine learning model of extubation for neurocritical care patients. Intensive Care Medicine. https://doi.org/10.1007/s00134-022-06922-8

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  2. Cinotti R, Mijangos JC, Pelosi P et al (2022) Extubation in neurocritical care patients: the ENIO international prospective study. Intens Care Med. https://doi.org/10.1007/s00134-022-06825-8

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Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, University of California, UCSF, 550 16Th St, San Francisco, CA, 94158, USA

    Romain Pirracchio

  2. Department of Anesthesia and Perioperative Care, University of California, Zuckerberg San Francisco General Hospital and Trauma Center, University of California San Francisco, 1001 Potrero Ave, San Francisco, CA, 94110, USA

    Romain Pirracchio

  3. Department of Anaesthesia and Critical Care, CHU Nantes, Nantes Université, Hôtel Dieu, 44000, Nantes, France

    Karim Asehnoune & Raphaël Cinotti

  4. UMR 1246 SPHERE “MethodS in Patients-Centered Outcomes and HEalth Research”, University of Nantes, University of Tours, INSERM, IRS2 22 Boulevard Benoni Goulin, 44200, Nantes, France

    Raphaël Cinotti

Authors
  1. Romain Pirracchio
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  2. Karim Asehnoune
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  3. Raphaël Cinotti
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Corresponding author

Correspondence to Karim Asehnoune.

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Pirracchio, R., Asehnoune, K. & Cinotti, R. Building a better machine learning model of extubation for neurocritical care patients. Author’s reply. Intensive Care Med 49, 121–122 (2023). https://doi.org/10.1007/s00134-022-06943-3

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  • DOI: https://doi.org/10.1007/s00134-022-06943-3

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