Wonngarm K, Lisa EV, Felicity TE et al (2018) The Changing Incidence and Presentation of Urinary Stones Over 3 Decades. Mayo Clin Proc 93(3)

Charles D Jr, Alexandria S, Janet CS, Christopher MH (2012) S S. Prevalence of kidney stones in the United States. Eur Urol 62(1)

Pietro Manuel F, Eric NT, Giovanni G, Gary CC (2013) Soda and other beverages and the risk of kidney stones. Clin J Am Soc Nephrol 8(8)

W G R MP (1982) D H M. Prevalence of urinary stone disease in vegetarians. Eur Urol 8(6)

Fredric LC, Andrew E, Elaine W (2005) Kidney stone disease. J Clin Invest 115(10)

Orson WM (2006) Kidney stones: pathophysiology and medical management. Lancet 367(9507)

Qi M, Li F, Rui S, Liang M, Guohai X, Yue C (2018) Uric acid stones, clinical manifestations and therapeutic considerations. Postgrad Med J 94(1114)

L DG GC, M L T AG (2004) R I, M C. Uric acid, phosphate and oxalate stones: treatment and prophylaxis. Urol Int (0)

Jolanta P, Marcin O (2016) Bacterially Induced formation of infectious urinary stones: recent developments and Future challenges. Curr Med Chem 24(3)

Margaret SP, David SG, Dean GA et al (2014) Medical management of kidney stones: AUA guideline. J Urol 192(2)

Tracy M, Nicole LM (2015) Treatment of the Infected Stone. Urol Clin North Am 42(4)

Michel D, Hassan B, Dominique B (2010) Composition and morphology of phosphate stones and their relation with etiology. Urol Res 38(6)

Benjamin WH, Jessica BW, Brian HE, Vernon M Jr (2013) P. Insurance status, stone composition, and 24-hour urine composition. J Endourol 27(5)

Neil SM, Ian CM, Ann M, K-M (2016) Accurate stone analysis: the impact on disease diagnosis and treatment. Urolithiasis 45(1)

Charlotte JH, Jeffrey MD (2023) Artificial Intelligence and Machine Learning in Clinical Medicine, 2023. N Engl J Med 388(13)

Eric JT (2019) High-performance medicine: the convergence of human and artificial intelligence. Nat Med 25(1)

Bhavneet B, Coryandar G, Neel SM, Olivier E (2021) Artificial Intelligence in Cancer Research and Precision Medicine. Cancer Discov 11(4)

Bob Y, Domenico V, Bhaskar KS (2020) Artificial intelligence in the diagnosis, treatment and prevention of urinary stones. Curr Opin Urol 30(6)

Kadir Y, Pinar Gundogan B, Muhammed T, Ozal Y, Murat K, Rajendra U (2021) A. Deep learning model for automated kidney stone detection using coronal CT images. Comput Biol Med 135(0)

Daniel CE, Evrim BT, Perry JP, Ronald MS (2022) A deep learning system for automated kidney stone detection and volumetric segmentation on noncontrast CT scans. Med Phys 49(4)

Erika JE-O, Brian HE, Dirk L, Robin G (2018) Current insights into the mechanisms and management of infection stones. Nat Rev Urol 16(1)

Flannigan R, Choy W, Chew B, Lange D (2014) Renal struvite stones–pathogenesis, microbiology, and management strategies. Nat Reviews Urol 11(6):333–341

Article  CAS  Google Scholar 

Helene J, Palle JSO (2014) Acute management of stones: when to treat or not to treat? World J Urol 33(2)

Wanni X, You-Lei F, Dongmei Z (2023) ResNet and its application to medical image processing: Research progress and challenges. Comput Methods Programs Biomed 240(0)

Asif S, Zhao M, Chen X, Zhu Y (2023) StoneNet: an efficient lightweight model based on depthwise separable convolutions for kidney stone detection from CT images. Interdisciplinary Sciences: Comput Life Sci 15(4):633–652

Google Scholar 

Zhu M, Li H, Chen H et al (2023) Segprompt: Boosting open-world segmentation via category-level prompt learning. Paper presented at: Proceedings of the IEEE/CVF International Conference on Computer Vision

Saeed RK, Margaret SP, William GR et al (2016) Kidney stones. Nat Rev Dis Primers 2(0)

Gina T, Annah V, William M, Vernon P (2021) Beyond prevalence: Annual cumulative incidence of kidney stones in the United States. J Urol 205(6)

Alexander JH, Spyridon PB, Patrick L et al (2021) Incidence of kidney stones in the United States: the Continuous National Health and Nutrition Examination Survey. J Urol 207(4)

Khashayar S, Naim MM, Bridget S (2012) Clinical review. Kidney stones 2012: pathogenesis, diagnosis, and management. J Clin Endocrinol Metab 97(6)

Api C, Gary C (2020) Trends in the prevalence of kidney stones in the United States from 2007 to 2016. Urolithiasis 49(1)

Louise S (2020) Assessing kidney stone composition using deep learning. Nat Rev Urol 17(4)

Leni Aziyus F, Freddy H, Hidetaka A et al (2020) Automated classification of urinary stones based on microcomputed tomography images using convolutional neural network. Phys Med 78(0)