6 -6 (92) 2026 - Mavlanov N.N., (Akhmedov Yu.M.) - INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN OPTIMIZING THE DIAGNOSIS AND THERAPEUTIC TACTICS OF NEPHROLITHIASIS IN CHILDREN: A SYSTEMATIC REVIEW

INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN OPTIMIZING THE DIAGNOSIS AND THERAPEUTIC TACTICS OF NEPHROLITHIASIS IN CHILDREN: A SYSTEMATIC REVIEW

Mavlanov N.N. - Samarkand State Medical University

(Akhmedov Yu.M.) - Samarkand State Medical University

Akhmedov I.Yu. - Samarkand State Medical University

Kholmurodov J.A. - Samarkand State Medical University

Resume

The selection of artificial intelligence (AI) strategies to optimize the diagnosis and management of pediatric nephrolithiasis represents a highly relevant scientific and practical challenge in modern endourology. This paper analyzes the high efficacy (94–99% accuracy) of AI, radiomics, and machine learning methods in stone detection and the prediction of surgical outcomes. The findings substantiate the critical role of neural networks in minimizing diagnostic errors and developing individualized therapeutic models for each patient. AI is evaluated as an innovative tool in urology that complements the clinician's practice.

Keywords: Urolithiasis, artificial intelligence, radiomics, machine learning, nephrolithiasis.

First page

27

Last page

32

For citation:Mavlanov N.N., (Akhmedov Yu.M.), Akhmedov I.Yu., Kholmurodov J.A. - INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN OPTIMIZING THE DIAGNOSIS AND THERAPEUTIC TACTICS OF NEPHROLITHIASIS IN CHILDREN: A SYSTEMATIC REVIEW//New Day in Medicine 6(92)2026 27-32 https://newdayworldmedicine.com/en/new_day_medicine/6-92-2026

List of References

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