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Lack of evidence and criteria to evaluate artificial intelligence and radiomics tools to be implemented in clinical settings

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Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Abbreviations

AI:

artificial intelligence

References

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Acknowledgments

We are thankful toward the authors Prof. Martina Sollini and colleagues of the article for the hard work they put on this field. We appreciate Dr. Jonathan Richard Bryan Bishop and Miss Rebecca Woolley for their kind suggestions and amendments of the English writing of the manuscript.

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Authors and Affiliations

  1. Department of Medical Statistics, Clinical Trials Unit, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhong Shan Er Road, Guangzhou, 510080, China

    Qian Zhou

  2. ESIEE Paris, Cité Descartes BP99, 93162, Noisy-le-Grand, France

    Yi-heng Cao

  3. Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhong Shan Er Road, Guangzhou, 510080, China

    Zhi-hang Chen

Authors
  1. Qian Zhou
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  2. Yi-heng Cao
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  3. Zhi-hang Chen
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Contributions

Qian Zhou: study design, article writing, final approval of the manuscript. Yi-heng Cao: study design, article writing, final approval of the manuscript. Zhi-hang Chen: study design, article writing, final approval of the manuscript.

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Correspondence to Qian Zhou.

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This article is part of the Topical Collection on Advanced Image Analyses (Radiomics and Artificial Intelligence)

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Zhou, Q., Cao, Yh. & Chen, Zh. Lack of evidence and criteria to evaluate artificial intelligence and radiomics tools to be implemented in clinical settings. Eur J Nucl Med Mol Imaging 46, 2812–2813 (2019). https://doi.org/10.1007/s00259-019-04493-3

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  • DOI: https://doi.org/10.1007/s00259-019-04493-3

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