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 LeePublished 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.