Database-based machine learning in sepsis deserves attention. Author's reply

Alexandre Kalimouttou¹, Romain Pirracchio^{2

3}

Affiliations

¹ Université Paris Cité and Université Sorbonne Paris Nord, Inserm UMR 1153, Center of Research in Epidemiology and Statistics (CRESS), ECSTRRA Team, 75004, Paris, France.
² Université Paris Cité and Université Sorbonne Paris Nord, Inserm UMR 1153, Center of Research in Epidemiology and Statistics (CRESS), ECSTRRA Team, 75004, Paris, France. Romain.Pirracchio@ucsf.edu.
³ Department of Anesthesia and Perioperative Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California San Francisco, 1001 Potrero Avenue, San Francisco, CA, 94910, USA. Romain.Pirracchio@ucsf.edu.

Comment

Alexandre Kalimouttou et al. Intensive Care Med. 2023 Feb.

. 2023 Feb;49(2):264-265.

doi: 10.1007/s00134-022-06972-y. Epub 2023 Jan 10.

Alexandre Kalimouttou¹, Romain Pirracchio^{2

3}

¹ Université Paris Cité and Université Sorbonne Paris Nord, Inserm UMR 1153, Center of Research in Epidemiology and Statistics (CRESS), ECSTRRA Team, 75004, Paris, France.
² Université Paris Cité and Université Sorbonne Paris Nord, Inserm UMR 1153, Center of Research in Epidemiology and Statistics (CRESS), ECSTRRA Team, 75004, Paris, France. Romain.Pirracchio@ucsf.edu.
³ Department of Anesthesia and Perioperative Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California San Francisco, 1001 Potrero Avenue, San Francisco, CA, 94910, USA. Romain.Pirracchio@ucsf.edu.

No abstract available

Comment on

Database-based machine learning in sepsis deserves attention.
Hu W, Yang M, Chen H. Hu W, et al. Intensive Care Med. 2023 Feb;49(2):262-263. doi: 10.1007/s00134-022-06961-1. Epub 2023 Jan 2. Intensive Care Med. 2023. PMID: 36592206 No abstract available.

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