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. 2023 Apr 1;207(7):853-854.
doi: 10.1164/rccm.202212-2284VP.

Artificial Intelligence for Early Sepsis Detection: A Word of Caution

Michiel Schinkel  1   2 , Tom van der Poll  1   3 , W Joost Wiersinga  1   3
Affiliations

Artificial Intelligence for Early Sepsis Detection: A Word of Caution

Michiel Schinkel et al. Am J Respir Crit Care Med. .
No abstract available

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Comment in

  • Introducing "Viewpoint: Turning the Air Blue".
    Martinez FJ, Bush A, Brochard L, Han MK, Chotirmall SH. Martinez FJ, et al. Am J Respir Crit Care Med. 2023 Apr 1;207(7):803. doi: 10.1164/rccm.202302-0241ED. Am J Respir Crit Care Med. 2023. PMID: 36753677 Free PMC article. No abstract available.

References

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    1. Evans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, et al. Surviving Sepsis Campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med . 2021;47:1181–1247. - PMC - PubMed
    1. Schinkel M, Paranjape K, Nannan Panday RS, Skyttberg N, Nanayakkara PWB. Clinical applications of artificial intelligence in sepsis: a narrative review. Comput Biol Med . 2019;115:103488. - PubMed
    1. Wong A, Otles E, Donnelly JP, Krumm A, McCullough J, DeTroyer-Cooley O, et al. External validation of a widely implemented proprietary sepsis prediction model in hospitalized patients. JAMA Intern Med . 2021;181:1065–1070. - PMC - PubMed
    1. Adams R, Henry KE, Sridharan A, Soleimani H, Zhan A, Rawat N, et al. Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis. Nat Med . 2022;28:1455–1460. - PubMed