Doumouchtsis SK, de Tayrac R, Lee J, Daly O, Melendez-Munoz J, Lindo FM, et al. An International Continence Society (ICS)/ International Urogynecological Association (IUGA) joint report on the terminology for the assessment and management of obstetric pelvic floor disorders. Int Urogynecol J. 2023;34(1):1–42. https://doi.org/10.1007/s00192-022-05397-x

Article  PubMed  Google Scholar 

Von Aarburg N, Veit-Rubin N, Boulvain M, Bertuit J, Simonson C, Desseauve D. Physical activity and urinary incontinence during pregnancy and postpartum: a systematic review and meta-analysis. Eur J Obstet Gyn R B. 2021;267:262–8. https://doi.org/10.1016/j.ejogrb.2021.11.005

Article  Google Scholar 

Giugale LE, Moalli PA, Canavan TP, Meyn LA, Oliphant SS. Prevalence and predictors of urinary incontinence at 1 year postpartum. Female Pelvic Med Rev. 2021;27(2):e436–41. https://doi.org/10.1097/SPV.0000000000000955

Article  Google Scholar 

Moossdorff-Steinhauser H, Berghmans B, Spaanderman M, Bols E. Prevalence, incidence and bothersomeness of urinary incontinence between 6 weeks and 1 year post-partum: a systematic review and meta-analysis. Int Urogynecol J. 2021;32(7):1675–93. https://doi.org/10.1007/s00192-021-04877-w

Article  PubMed  PubMed Central  Google Scholar 

Hage-Fransen M, Wiezer M, Otto A, Wieffer-Platvoet MS, Slotman MH, Nijhuis-van DSM, et al. Pregnancy- and obstetric-related risk factors for urinary incontinence, fecal incontinence, or pelvic organ prolapse later in life: a systematic review and meta-analysis. ACTA Obstet Gyn Scan. 2021;100(3):373–82. https://doi.org/10.1111/aogs.14027

Article  Google Scholar 

MacArthur C, Wilson D, Herbison P, Lancashire RJ, Hagen S, Toozs-Hobson P et al. Urinary incontinence persisting after childbirth: extent, delivery history, and effects in a 12-year longitudinal cohort study. BJOG: An International Journal of Obstetrics & Gynaecology. 2016;123(6):1022–9. https://doi.org/10.1111/1471-0528.13395.

AlQuaiz AM, Kazi A, AlYousefi N, Alwatban L, AlHabib Y, Turkistani I. Urinary incontinence affects the quality of life and increases psychological distress and low self-esteem. Healthcare-Basel. 2023;11(12). https://doi.org/10.3390/healthcare11121772

Chisholm LP, Sebesta EM, Gleicher S, Kaufman M, Dmochowski RR, Reynolds WS. The burdens of incontinence: quantifying incontinence product usage and costs in women. Neurourol Urodynam. 2022;41(7):1601–11. https://doi.org/10.1002/nau.25007

Article  Google Scholar 

Rashidi FF, Hajian S, Darvish S, Alavi MH. Predictors of help-seeking behaviors in women with urinary incontinence: based on Iranian women’s lens. PLoS ONE. 2023;18(8): e289785. https://doi.org/10.1371/journal.pone.0289785

Article  CAS  Google Scholar 

Rashidi FF, Hajian S, Darvish S, Alavi MH. Explaining factors affecting help-seeking behaviors in women with urinary incontinence: a qualitative study. BMC Health Serv Res. 2021;21(1):60. https://doi.org/10.1186/s12913-020-06047-y

Article  Google Scholar 

Sigurdardottir T, Steingrimsdottir T, Geirsson RT, Halldorsson TI, Aspelund T, Bø K. Can postpartum pelvic floor muscle training reduce urinary and anal incontinence?: an assessor-blinded randomized controlled trial. Am J Obstet Gynecol. 2020;222(3):241–7. https://doi.org/10.1016/j.ajog.2019.09.011

Article  Google Scholar 

Liu W, Qian L. Establishment and validation of a risk prediction model for postpartum stress urinary incontinence based on pelvic floor ultrasound and clinical data. Int Urogynecol J. 2022;33(12):3491–7. https://doi.org/10.1007/s00192-022-05395-z

Article  PubMed  PubMed Central  Google Scholar 

Jelovsek JE, Piccorelli A, Barber MD, Tunitsky-Bitton E, Kattan MW. Prediction models for postpartum urinary and fecal incontinence in primiparous women. Female Pelvic Med Reconstr Surg. 2013;19(2):110–8. https://doi.org/10.1097/SPV.0b013e31828508f0

Article  PubMed  Google Scholar 

Baracho SM, Da Silva LB, Baracho E, Da Silva Filho AL, Sampaio RF, De Figueiredo EM. Pelvic floor muscle strength predicts stress urinary incontinence in primiparous women after vaginal delivery. Int Urogynecol J. 2012;23(7):899–906. https://doi.org/10.1007/s00192-012-1681-7

Article  PubMed  Google Scholar 

Krishnan R, Rajpurkar P, Topol EJ. Self-supervised learning in medicine and healthcare. NAT Biomed Eng. 2022;6(12):1346–52. https://doi.org/10.1038/s41551-022-00914-1

Article  PubMed  Google Scholar 

Ngiam KY, Khor IW. Big data and machine learning algorithms for health-care delivery. Lancet Oncol. 2019;20(5):e262–73. https://doi.org/10.1016/S1470-2045(19)30149-4

Article  PubMed  Google Scholar 

Guan C, Gong A, Zhao Y, Yin C, Geng L, Liu L, et al. Interpretable machine learning model for new-onset atrial fibrillation prediction in critically ill patients: a multi-center study. Crit Care. 2024;28(1):349. https://doi.org/10.1186/s13054-024-05138-0

Article  PubMed  PubMed Central  Google Scholar 

Huang L, Zhang SW, Wu SL, Ma L, Deng XH. The Chinese version of ICIQ: a useful tool in clinical practice and research on urinary incontinence. Neurourol Urodynam. 2008;27(6):522–4. https://doi.org/10.1002/nau.20546

Article  Google Scholar 

Legendre B, Cerasuolo D, Dejardin O, Boyer A. How to deal with missing data? Multiple imputation by chained equations: recommendations and explanations for clinical practice. Nephrol Ther. 2023;19(3):171–9. https://doi.org/10.1684/ndt.2023.24

Article  PubMed  Google Scholar 

Dablain D, Krawczyk B, Chawla NV. DeepSMOTE: fusing deep learning and SMOTE for imbalanced data. IEEE T Neur Net Lear. 2023;34(9):6390–404. https://doi.org/10.1109/TNNLS.2021.3136503

Article  Google Scholar 

Xie H, Tang Q, Zhu Q. A multiplier bootstrap approach to designing robust algorithms for contextual bandits. IEEE T Neur Net Lear. 2023;34(12):9887–99. https://doi.org/10.1109/TNNLS.2022.3161806

Article  Google Scholar 

Liu Y, Liao S, Jiang S, Ding L, Lin H, Wang W. Fast cross-validation for Kernel-based algorithms. IEEE T Pattern Anal. 2020;42(5):1083–96. https://doi.org/10.1109/TPAMI.2019.2892371

Article  Google Scholar 

Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ-Brit Med J. 2015;350(jan07 4):g7594. https://doi.org/10.1136/bmj.g7594

Zambrano GL, Buckheit C, Kuller JA, Gray B, Dotters-Katz S. Evidence based management of labor. Obstet Gynecol Surv. 2024;79(1):39–53. https://doi.org/10.1097/OGX.0000000000001225

Article  Google Scholar