Predictive Modeling of Urinary Stone Composition Using Machine Learning and Clinical Data: Implications for Treatment Strategies and Pathophysiological Insights.
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| Title: | Predictive Modeling of Urinary Stone Composition Using Machine Learning and Clinical Data: Implications for Treatment Strategies and Pathophysiological Insights. |
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| Authors: | Chmiel JA; Department of Microbiology and Immunology, Western University, London, Canada.; Canadian Centre for Human Microbiome and Probiotic Research, London, Canada., Stuivenberg GA; Department of Microbiology and Immunology, Western University, London, Canada.; Canadian Centre for Human Microbiome and Probiotic Research, London, Canada., Wong JFW; Division of Urology, Department of Surgery, Western University, London, Canada., Nott L; Division of Urology, Department of Surgery, Western University, London, Canada., Burton JP; Department of Microbiology and Immunology, Western University, London, Canada.; Canadian Centre for Human Microbiome and Probiotic Research, London, Canada.; Division of Urology, Department of Surgery, Western University, London, Canada., Razvi H; Division of Urology, Department of Surgery, Western University, London, Canada., Bjazevic J; Division of Urology, Department of Surgery, Western University, London, Canada. |
| Source: | Journal of endourology [J Endourol] 2024 Aug; Vol. 38 (8), pp. 778-787. Date of Electronic Publication: 2024 May 30. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Mary Ann Liebert Country of Publication: United States NLM ID: 8807503 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1557-900X (Electronic) Linking ISSN: 08927790 NLM ISO Abbreviation: J Endourol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1557-900X |
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| DOI: | 10.1089/end.2023.0446 |
