Artificial intelligence for planning patient management tactics after percutaneous nephrolithotripsy

Автор: Shchamkhalova K.K., Merinov D.S., Artemov A.V., Gurbanov Sh.sh., Apolikhin O.I., Kaprin A.D.

Журнал: Экспериментальная и клиническая урология @ecuro

Рубрика: Экспериментальная урология

Статья в выпуске: 3 т.17, 2024 года.

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Introduction. Urolithiasis remains one of the most common urological pathologies that deserves due attention in the healthcare system. A current direction in optimizing percutaneous nephrolithotripsy (PCNL) is a personalized prognosis for patient management based on artificial intelligence (AI) decisionmaking algorithms. In our work, we applied an algorithm to create the most optimal tactics for patient management after PCNL.

Urolithiasis, percutaneous nephrolithotripsy, artificial intelligence

Короткий адрес: https://sciup.org/142243274

IDR: 142243274   |   DOI: 10.29188/2222-8543-2024-17-3-43-51

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