A Study on the Optimal Artificial Intelligence Model for Determination of Urolithiasis

Sung-Jong Eun, Myoung Suk Yun, Taeg-Keun Whangbo, Khae-Hawn Kim

Open source

DOI: 10.5213/inj.2244202.101
Published: 2022-09-30
Container: International Neurourology Journal
Publisher: Korean Continence Society
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.5213/inj.2244202.101,
  title = {A Study on the Optimal Artificial Intelligence Model for Determination of Urolithiasis},
  author = {Sung-Jong Eun and Myoung Suk Yun and Taeg-Keun Whangbo and Khae-Hawn Kim},
  year = {2022},
  journal = {International Neurourology Journal},
  doi = {10.5213/inj.2244202.101},
  url = {https://doi.org/10.5213/inj.2244202.101}
}

RIS

TY  - JOUR
TI  - A Study on the Optimal Artificial Intelligence Model for Determination of Urolithiasis
AU  - Sung-Jong Eun
AU  - Myoung Suk Yun
AU  - Taeg-Keun Whangbo
AU  - Khae-Hawn Kim
PY  - 2022
JO  - International Neurourology Journal
DO  - 10.5213/inj.2244202.101
UR  - https://doi.org/10.5213/inj.2244202.101
ER  -

APA

Eun, S., Yun, M. S., Whangbo, T., & Kim, K. (2022). A Study on the Optimal Artificial Intelligence Model for Determination of Urolithiasis. International Neurourology Journal. https://doi.org/10.5213/inj.2244202.101

Source records

crossref · retrieved 2026-09-26T22:05:41.654Z