1. Inflammation indexes and machine-learning algorithm in predicting urethroplasty success
- Author
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Emre Tokuc, Mithat Eksi, Ridvan Kayar, Samet Demir, Ramazan Topaktas, Yavuz Bastug, Mehmet Akyuz, and Metin Ozturk
- Subjects
artificial intelligence ,biomarkers ,urethral stricture ,urethra ,Diseases of the genitourinary system. Urology ,RC870-923 - Abstract
Purpose: To assess the predictive capability of hematological inflammatory markers for urethral stricture recurrence after primary urethroplasty and to compare traditional statistical methods with a machine-learning-based artificial intelligence algorithm. Materials and Methods: Two hundred eighty-seven patients who underwent primary urethroplasty were scanned. Ages, smoking status, comorbidities, hematological inflammatory parameters (neutrophil-lymphocyte ratios, platelet-lymphocyte ratios [PLR], systemic immune-inflammation indexes [SII], and pan-immune-inflammation values [PIV]), stricture characteristics, history of previous direct-visual internal urethrotomy, urethroplasty techniques, and grafts/flaps placements were collected. Patients were followed up for one year for recurrence and grouped accordingly. Univariate and multivariate logistic regression analyses were conducted to create a predictive model. Additionally, a machine-learning-based logistic regression analysis was implemented to compare predictive performances. p
- Published
- 2024
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