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Development of prediction models of spontaneous ureteral stone passage through machine learning: Comparison with conventional statistical analysis.

Jee Soo ParkDong Wook KimDongu LeeTaeju LeeKyo Chul KooWoong Kyu HanByung Ha ChungKwang-Suk Lee
Published in: PloS one (2021)
SSP prediction models were developed in patients with well-controlled unilateral ureteral stones; the performance of the models was good, especially in identifying SSP for 5-10-mm ureteral stones without definite treatment guidelines. To further improve the performance of these models, future studies should focus on using machine learning techniques in image analysis.
Keyphrases
  • machine learning
  • editorial comment
  • clinical practice
  • case control