nach oben

Intensive Care Medicine

Erschienen in:

01.02.2020 | Editorial

Clinical management of sepsis can be improved by artificial intelligence: yes

verfasst von: Matthieu Komorowski

Erschienen in: Intensive Care Medicine | Ausgabe 2/2020

Einloggen, um Zugang zu erhalten

Excerpt

The management of sepsis is a highly complex, multifaceted challenge that remains the realm of highly skilled and trained human experts. But as medical applications of artificial intelligence continue to pour in, it is becoming obvious that some of these decisions could soon be left to machines that could be dubbed “intelligent”, improving clinical practice and patient outcomes [1]. Indeed, most of the tasks involved in the clinical management of sepsis (early recognition, selection of antibiotic therapy, haemodynamic optimisation, etc.) could be individually performed or optimised by dedicated algorithms. …

Topol EJ (2019) High-performance medicine: the convergence of human and artificial intelligence. Nat Med 25:44. https://doi.org/10.1038/s41591-018-0300-7 CrossRefPubMed

Islam MM, Nasrin T, Walther BA et al (2019) Prediction of sepsis patients using machine learning approach: a meta-analysis. Comput Methods Programs Biomed 170:1–9. https://doi.org/10.1016/j.cmpb.2018.12.027 CrossRefPubMed

Mao Q, Jay M, Hoffman JL et al (2018) Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU. BMJ Open 8:e017833. https://doi.org/10.1136/bmjopen-2017-017833 CrossRefPubMedPubMedCentral

Shimabukuro DW, Barton CW, Feldman MD et al (2017) Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial. BMJ Open Respir Res 4:e000234. https://doi.org/10.1136/bmjresp-2017-000234 CrossRefPubMedPubMedCentral

Donnelly JP, Safford MM, Shapiro NI et al (2017) Application of the Third International Consensus Definitions for Sepsis (Sepsis-3) Classification: a retrospective population-based cohort study. Lancet Infect Dis 17:661–670. https://doi.org/10.1016/S1473-3099(17)30117-2 CrossRefPubMedPubMedCentral

Seymour CW, Kennedy JN, Wang S et al (2019) Derivation, validation, and potential treatment implications of novel clinical phenotypes for sepsis. JAMA 321:2003–2017. https://doi.org/10.1001/jama.2019.5791 CrossRefPubMedPubMedCentral

Antcliffe DB, Burnham KL, Al-Beidh F et al (2018) Transcriptomic signatures in sepsis and a differential response to steroids: from the VANISH randomized trial. Am J Respir Crit Care Med. https://doi.org/10.1164/rccm.201807-1419OC CrossRef

Komorowski M, Celi LA, Badawi O et al (2018) The artificial intelligence clinician learns optimal treatment strategies for sepsis in intensive care. Nat Med 24:1716. https://doi.org/10.1038/s41591-018-0213-5 CrossRefPubMed

Waschka A, Komorowski M, Hubbard A, Pirracchio R (2019) Optimal timing to vasopressor initiation in septic shock: revisiting SEPSIS-3 guidelines using machine learning. Intensive Care Med Exp 7(Suppl 3):001685

10.

Gottesman O, Johansson F, Meier J, et al (2018) Evaluating reinforcement learning algorithms in observational health settings. arXiv:1805.12298 [cs, stat]

11.

Coiera E (2019) The last mile: where artificial intelligence meets reality. J Med Internet Res 21:e16323. https://doi.org/10.2196/16323 CrossRefPubMedPubMedCentral

12.

International Civil Aviation Organization (2013) ICAO 9365—manual of all-weather operations. International Civil Aviation Organization, Montreal

Titel: Clinical management of sepsis can be improved by artificial intelligence: yes
verfasst von: Matthieu Komorowski
Publikationsdatum: 01.02.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Intensive Care Medicine / Ausgabe 2/2020
Print ISSN: 0342-4642
Elektronische ISSN: 1432-1238
DOI: https://doi.org/10.1007/s00134-019-05898-2

Update AINS

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

hier abonnieren

Springer Medizin

Clinical management of sepsis can be improved by artificial intelligence: yes

Excerpt

Neu im Fachgebiet AINS

Bei schweren Reaktionen auf Insektenstiche empfiehlt sich eine spezifische Immuntherapie

Hinter dieser Appendizitis steckte ein Erreger

Ärztliche Empathie hilft gegen Rückenschmerzen

Mehr Schaden als Nutzen durch präoperatives Aussetzen von GLP-1-Agonisten?

Update AINS

Springer Medizin

Excerpt

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 2/2020

The zero-VAP sophistry and controversies surrounding prevention of ventilator-associated pneumonia

Extra-cardiac endovascular infections in the critically ill

Bloodstream infections in critically ill patients: an expert statement

Treatment of Ebola-related critical illness

Antibiotic prophylaxis in the ICU: to be or not to be administered for patients undergoing procedures?

Post-operative abdominal infections: epidemiology, operational definitions, and outcomes

Neu im Fachgebiet AINS

Bei schweren Reaktionen auf Insektenstiche empfiehlt sich eine spezifische Immuntherapie

Hinter dieser Appendizitis steckte ein Erreger

Ärztliche Empathie hilft gegen Rückenschmerzen

Mehr Schaden als Nutzen durch präoperatives Aussetzen von GLP-1-Agonisten?

Update AINS