urovestВестник урологииUrology Herald2308-6424Rostov State Medical University10.21886/2308-6424-2024-12-4-91-101urovest-909Research ArticleОБЗОРЫ ЛИТЕРАТУРЫREVIEWS ARTICLEНейросети в онкоурологииNeural networks in oncourologyhttps://orcid.org/0000-0001-8060-6691КорчагинМ. П.KorchaginM. P.

Корчагин Михаил Павлович.

Москва

Mikhail P. Korchagin.

Moscow

mihailsun@mail.ruhttps://orcid.org/0000-0003-3299-0574ГоворовА. В.GovorovA. V.

Говоров Александр Викторович — д-р мед. наук.

Москва

Alexander V. Govorov — Dr.Sc.(Med).

Moscow

dr.govorov@gmail.comhttps://orcid.org/0000-0001-5468-0011ВасильевА. О.VasilyevA. O.

Васильев Александр Олегович — канд. мед. наук.

Москва

Alexander O. Vasilyev — Cand.Sc.(Med).

Moscow

alexvasilyev@me.comhttps://orcid.org/0000-0002-4708-1683ГрицковИ. О.GritskovI. O.

Грицков Игорь Олегович.

Москва

Igor O. Gritskov.

Moscow

grickoff@mail.ruhttps://orcid.org/0000-0002-6096-5723ПушкарьД. Ю.PushkarD. Yu.

Пушкарь Дмитрий Юрьевич — акад. РАН, д-р мед. наук, профессор.

Москва

Dmitry Yu. Pushkar — Dr.Sc.(Med), Full Prof., Acad. of the RAS.

Moscow

pushkardm@mail.ruРоссийский университет медициныРоссияRussian University of MedicineRussian FederationРоссийский университет медицины; Городская клиническая больница им. С.П. БоткинаРоссияRussian University of Medicine; Botkin City Clinical HospitalRussian Federation20240509202412491101Copyright © Корчагин М.П., Говоров А.В., Васильев А.О., Грицков И.О., Пушкарь Д.Ю., 20242024Корчагин М.П., Говоров А.В., Васильев А.О., Грицков И.О., Пушкарь Д.Ю.Korchagin M.P., Govorov A.V., Vasilyev A.O., Gritskov I.O., Pushkar D.Y.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.urovest.ru/jour/article/view/909

В последние годы нейросети стали широко применяться во многих областях науки и медицины, включая онкологию. Одной из ключевых проблем в онкоурологии является точная и ранняя диагностика злокачественных новообразований. Нейросети позволяют анализировать множество медицинских данных и выявлять взаимосвязи между качественными и количественными признаками, что способствует более точной и своевременной диагностике. Более того, нейросети могут использоваться для прогнозирования прогрессирования опухоли, оценки эффективности лечения и оптимизации плана лечения для каждого пациента. В онкоурологии использование нейросетей предоставляет новые перспективы для диагностики, прогнозирования и лечения различных опухолей органов мочеполовой системы. В обзорной статье представлены способы применения нейросетей в онкоурологии. Приведены исследования, посвящённые использованию нейросетей для диагностики, прогнозирования и лечения онкологических заболеваний урологического профиля. Продемонстрированы преимущества и ограничения использования нейросетей в этой области и предложены возможные направления для будущих исследований. Сделаны выводы о том, что применение нейросетей в онкоурологии открывает горизонты для развития персонализированного подхода к диагностике и лечению онкологических заболеваний. Искусственный интеллект может стать мощным инструментом для улучшения прогнозирования результатов лечения пациентов, а также сокращения нежелательных побочных эффектов терапии. Внедрение нейросетей в онкоурологическую практику открывает новые возможности для улучшения работы, организации здравоохранения и качества оказания медицинской помощи пациентам.

In recent decades, neural networks have been widely applied in many fields of science and medicine. Accurate and early diagnosis of malignancies is a key challenge in oncology. Neural networks can analyse a wide range of medical data and identify relationships between qualitative and quantitative features. This allows for more precise and timely diagnoses. Moreover, they can be used to predict tumour progression, evaluate treatment effectiveness, and optimise treatment plans for each patient

In oncourology, the use of neural networks offers new perspectives for the diagnosis, prognosis, and treatment of various cancer conditions related to the urinary tract and male reproductive system. This review article explores how neural networks are being used in this field and present research into the use of neural networks for diagnosing, predicting the course and treating urological oncological diseases. The advantages and limitations of using neural networks in this field are demonstrated, and possible directions for future research are suggested. The application of neural networks in oncourology opens new horizons for the development of a personalised approach to diagnosing and treating oncological diseases. Artificial intelligence has the potential to become a powerful tool for improving the accuracy of patient outcome predictions and reducing undesirable side effects of therapy. Introducing neural networks into oncourological practice creates new opportunities for enhancing the work of healthcare organisations and improving the quality of care provided to patients. This can lead to better treatment outcomes and improved patient satisfaction.

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The authors declare that there are no conflicts of interest present.