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The prospect of machine learning in predicting post-lithotripsy outcomes

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References

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Funding

No grants or funding was provided for this study.

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Authors and Affiliations

  1. Department of Urology, Minimally Invasive Surgery Center, The First Affiliated Hospital of Guangzhou Medical University, Kangda Road 1, Haizhu District, Guangzhou, 510230, China

    Linjie Peng, Jinyou Pan, Ding Yang & Wen Zhong

  2. Guangdong Key Laboratory of Urology, Guangzhou, China

    Linjie Peng, Jinyou Pan, Ding Yang & Wen Zhong

  3. Guangzhou Institute of Urology, Guangzhou, China

    Linjie Peng, Jinyou Pan, Ding Yang & Wen Zhong

Authors
  1. Linjie Peng
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  2. Jinyou Pan
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  3. Ding Yang
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  4. Wen Zhong
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Contributions

LP and WZ participated in project development, manuscript writing and editing, JP and YD participated in manuscript writing and related articles searching.

Corresponding author

Correspondence to Wen Zhong.

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Peng, L., Pan, J., Yang, D. et al. The prospect of machine learning in predicting post-lithotripsy outcomes. World J Urol 39, 4287–4288 (2021). https://doi.org/10.1007/s00345-020-03377-8

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  • DOI: https://doi.org/10.1007/s00345-020-03377-8

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