Okui N, Erel T, Okui MA (2023) Analysis of predictive factors for return to sports in female athletes with stress urinary incontinence. Cureus 15:e44364. https://doi.org/10.7759/cureus.44364

Article  PubMed  PubMed Central  Google Scholar 

Okui N, Ikegami T, Mikic AN, Okui M, Gaspar A (2023) Long-term improvement in urinary incontinence in an elite female athlete through laser treatment: a case report. Cureus 15:e36730. https://doi.org/10.7759/cureus.36730

Article  PubMed  PubMed Central  Google Scholar 

Rodrigues MP, Berube ME, Charette M, Mclean L (2024) Conservative interventions for female exercise-induced urinary incontinence: a systematic review. BJU Int. https://doi.org/10.1111/bju.16474

Article  Google Scholar 

Barbosa P, Rodrigues MP, e Silva AAC, e Silva MPM (2024) Prevalence of urinary incontinence in Brazilian para athletes. Br J Sports Med 58:bjsports-2024-108076. https://doi.org/10.1136/bjsports-2024-108076

Article  Google Scholar 

Nose-Ogura S, Yoshino O, Nakamura-Kamoto H et al (2023) Medical issues for female athletes returning to competition after childbirth. Phys Sportsmed. https://doi.org/10.1080/00913847.2023.2188395

Article  PubMed  Google Scholar 

Casey EK, Temme K (2017) Pelvic floor muscle function and urinary incontinence in the female athlete. Phys Sportsmed 45:399–407. https://doi.org/10.1080/00913847.2017.1372677

Article  PubMed  Google Scholar 

Pires TF, Pires PM, Moreira MH et al (2020) Pelvic floor muscle training in female athletes: a randomized controlled pilot study. Int J Sports Med 41:264–270. https://doi.org/10.1055/a-1073-7977

Article  PubMed  Google Scholar 

Dakic JG, Hay-Smith J, Lin KY et al (2023) Experience of playing sport or exercising for women with pelvic floor symptoms: a qualitative study. Sports Med Open 9:25. https://doi.org/10.1186/s40798-023-00565-9

Article  PubMed  PubMed Central  Google Scholar 

Hilde G, Stær-Jensen J, Siafarikas F et al (2023) Postpartum pelvic floor muscle training, levator ani avulsion and levator hiatus area: a randomized trial. Int Urogynecol J 34:413–423. https://doi.org/10.1007/s00192-022-05406-z

Article  PubMed  Google Scholar 

Woodley SJ, Lawrenson P, Boyle R et al (2020) Pelvic floor muscle training for preventing and treating urinary and faecal incontinence in antenatal and postnatal women. Cochrane Database Syst Rev 5:CD007471. https://doi.org/10.1002/14651858.CD007471.pub4

Article  PubMed  Google Scholar 

Okui N (2019) Efficacy and safety of non-ablative vaginal erbium:YAG laser treatment as a novel surgical treatment for overactive bladder syndrome: comparison with anticholinergics and β3-adrenoceptor agonists. World J Urol 37:2459–2466. https://doi.org/10.1007/s00345-019-02644-7

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ford AA, Rogerson L, Cody JD et al (2017) Mid-urethral sling operations for stress urinary incontinence in women. Cochrane Database Syst Rev 7:CD006375. https://doi.org/10.1002/14651858.CD006375.pub4

Article  PubMed  Google Scholar 

Okui N (2024) The potential of non-ablative erbium (YAG) laser treatment for complications after midurethral sling surgery: a narrative review. Cureus 16:e58486. https://doi.org/10.7759/cureus.58486

Article  PubMed  PubMed Central  Google Scholar 

Okui N (2024) Unsupervised machine learning reveals a vulvodynia-predominant subtype in bladder pain syndrome/interstitial cystitis. Cureus 16:e62585. https://doi.org/10.7759/cureus.62585

Article  PubMed  PubMed Central  Google Scholar 

Okui N (2024) Navigating treatment choices for stress and urgency urinary incontinence using graph theory in discrete mathematics. Cureus 16:e61315. https://doi.org/10.7759/cureus.61315

Article  PubMed  PubMed Central  Google Scholar 

Okui N (2024) Innovative decision making tools using discrete mathematics for stress urinary incontinence treatment. Sci Rep 14:9900. https://doi.org/10.1038/s41598-024-60407-w

Article  CAS  PubMed  PubMed Central  Google Scholar 

Okui N (2019) Comparison between erbium-doped yttrium aluminum garnet laser therapy and sling procedures in the treatment of stress and mixed urinary incontinence. World J Urol 37:885–889. https://doi.org/10.1007/s00345-018-2445-x

Article  PubMed  Google Scholar 

Dindorf C, Bartaguiz E, Gassmann F, Fröhlich M (2022) Conceptual structure and current trends in artificial intelligence, machine learning, and deep learning research in sports: a bibliometric review. Int J Environ Res Public Health 20:173. https://doi.org/10.3390/ijerph20010173

Article  PubMed  PubMed Central  Google Scholar 

Obama B (2016) United States health care reform: progress to date and next steps. JAMA 316:525–532. https://doi.org/10.1001/jama.2016.9797

Article  PubMed  PubMed Central  Google Scholar 

Gotoh M, Asakura H, Takei M et al (2019) Clinical edition, 2nd ed. The Japanese Continence Society, The Japanese Urological Association

Harada D, Asanoi H, Noto T, Takagawa J (2020) Different pathophysiology and outcomes of heart failure with preserved ejection fraction stratified by K-means clustering. Front Cardiovasc Med 7:607760. https://doi.org/10.3389/fcvm.2020.607760

Article  CAS  PubMed  PubMed Central  Google Scholar 

Harada D, Asanoi H, Noto T, Takagawa J (2020) The impact of right ventricular dysfunction on the effectiveness of beta-blockers in heart failure with preserved ejection fraction. J Cardiol 76:325–334. https://doi.org/10.1016/j.jjcc.2020.05.001

Article  PubMed  Google Scholar 

Guazzi M, Dixon D, Labate V et al (2017) RV contractile function and its coupling to pulmonary circulation in heart failure with preserved ejection fraction: stratification of clinical phenotypes and outcomes. JACC Cardiovasc Imaging 10:1211–1221. https://doi.org/10.1016/j.jcmg.2016.12.024

Article  PubMed  Google Scholar 

Mohammadi T, D’Ascenzo F, Pepe M et al (2023) Unsupervised machine learning with cluster analysis in patients discharged after an acute coronary syndrome: insights from a 23,270-patient study. Am J Cardiol 193:44–51. https://doi.org/10.1016/j.amjcard.2023.01.048

Article  PubMed  Google Scholar 

Lenz A, Bahr F, Riedel C et al (2024) Cluster analysis of 100 Marfan patients based on aortic 4D flow MRI and Z-score: insights into disease heterogeneity and stratification of subgroups. Eur Radiol. https://doi.org/10.1007/s00330-024-11034-6

Article  PubMed  Google Scholar 

Flores AM, Schuler A, Eberhard AV et al (2021) Unsupervised learning for automated detection of coronary artery disease subgroups. J Am Heart Assoc 10:e021976. https://doi.org/10.1161/JAHA.121.021976

Article  PubMed  PubMed Central  Google Scholar 

Hoefnagel SJM, Koemans WJ, Khan HN et al (2022) Identification of novel molecular subgroups in esophageal adenocarcinoma to predict response to neo-adjuvant therapies. Cancers (Basel) 14:4498. https://doi.org/10.3390/cancers14184498

Article  CAS  PubMed  Google Scholar 

Ling C, Zhou X, Gao Y, Sui X (2022) Identification of immune subtypes of esophageal adenocarcinoma to predict prognosis and immunotherapy response. Pharmaceuticals (Basel) 15:605. https://doi.org/10.3390/ph15050605

Article  CAS  PubMed  Google Scholar 

Chan C, Law BMH, So W, Chow K, Waye M (2017) Novel strategies on personalized medicine for breast cancer treatment: an update. Int J Mol Sci 18:2423. https://doi.org/10.3390/ijms18112423

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lumachi F, Chiara GB, Foltran L, Basso SM (2015) Proteomics as a guide for personalized adjuvant chemotherapy in patients with early breast cancer. Cancer Genomics Proteomics 12:385–390 (PMID: 26543084)

CAS  PubMed  Google Scholar 

Liang M, Huang J, Liu C, Chen M (2024) Predictive modeling of long-term prognosis after resection in typical pulmonary carcinoid: a machine learning perspective. Cancer Investig 42:544–558. https://doi.org/10.1080/07357907.2024.2356002