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Editorial
. 2024 Sep;9(3):518-520.
doi: 10.1177/23969873241275863.

Artificial intelligence, machine learning, and reproducibility in stroke research

Michele Romoli  1 , Pietro Caliandro  2
Affiliations
Editorial

Artificial intelligence, machine learning, and reproducibility in stroke research

Michele Romoli et al. Eur Stroke J. 2024 Sep.
No abstract available

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Conflict of interest statement

Declaration of conflicting interestThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: MR is supported by Young Investigator Grants from the Italian Stroke Association (ISA-AII), and declares support for educational activities from CLS-Behring and PRESTIGE-AF trial.

References

    1. Nagel S, Sinha D, Day D, et al. E-ASPECTS software is non-inferior to neuroradiologists in applying the ASPECT score to computed tomography scans of acute ischemic stroke patients. Int J Stroke 2017; 12: 615–622. - PubMed
    1. Kellner E, Reisert M, Kiselev VG, et al. Automated infarct core volumetry within the hypoperfused tissue: technical implementation and evaluation. J Comput Assist Tomogr 2017; 41: 515–520. - PubMed
    1. van Leeuwen KG, Meijer FJA, Schalekamp S, et al. Cost-effectiveness of artificial intelligence aided vessel occlusion detection in acute stroke: an early health technology assessment. Insights Imaging 2021; 12: 133. - PMC - PubMed
    1. Chen Y, Tozer DJ, Liu W, et al. Prediction of response to thrombolysis in acute stroke using neural network analysis of CT perfusion imaging. Eur Stroke J 2023; 8: 629–637. - PMC - PubMed
    1. Monteiro M, Fonseca AC, Freitas AT, et al. Using machine learning to improve the prediction of functional outcome in ischemic stroke patients. IEEE/ACM Trans Comput Biol Bioinform 2018; 15: 1953–1959. - PubMed

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