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Editorial
. 2020 Jun;75(6):965-967.
doi: 10.1053/j.ajkd.2019.08.010. Epub 2019 Oct 31.

Machine Learning to Predict Acute Kidney Injury

Affiliations
Editorial

Machine Learning to Predict Acute Kidney Injury

F Perry Wilson. Am J Kidney Dis. 2020 Jun.
No abstract available

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Conflict of interest statement

Financial Disclosure: The author declares that he has no relevant financial interests.

Comment on

  • A clinically applicable approach to continuous prediction of future acute kidney injury.
    Tomašev N, Glorot X, Rae JW, Zielinski M, Askham H, Saraiva A, Mottram A, Meyer C, Ravuri S, Protsyuk I, Connell A, Hughes CO, Karthikesalingam A, Cornebise J, Montgomery H, Rees G, Laing C, Baker CR, Peterson K, Reeves R, Hassabis D, King D, Suleyman M, Back T, Nielson C, Ledsam JR, Mohamed S. Tomašev N, et al. Nature. 2019 Aug;572(7767):116-119. doi: 10.1038/s41586-019-1390-1. Epub 2019 Jul 31. Nature. 2019. PMID: 31367026 Free PMC article.

References

    1. Parkins D The world’s most valuable resource is no longer oil, but data. Economist. 2017.
    1. Tomasev N, Glorot X, Rae JW, et al. A clinically applicable approach to continuous prediction of future acute kidney injury. Nature. 2019;572(7767):116–119. - PMC - PubMed
    1. Simonov M, Ugwuowo U, Moreira E, et al. A simple real-time model for predicting acute kidney injury in hospitalized patients in the US: a descriptive modeling study. PLoS Med. 2019;16(7):e1002861. - PMC - PubMed
    1. Koyner JL, Carey KA, Edelson DP, Churpek MM. The development of a machine learning inpatient acute kidney injury prediction model. Crit Care Med. 2018;46(7):1070–1077. - PubMed
    1. Choi E, Schuetz A, Stewart WF, Sun J. Using recurrent neural network models for early detection of heart failure onset. J Am Med Inform Assoc. 2016;24(2):361–370. - PMC - PubMed