References

asurgery

Амбулаторная хирургия

Ambulatornaya khirurgiya = Ambulatory Surgery (Russia)

2712-87412782-2591

ООО «ГРУППА РЕМЕДИУМ»

10.21518/akh2026-005

asurgery-621

Research Article

ФЛЕБОЛОГИЯ

PHLEBOLOGY

Потенциал методов искусственного интеллекта при заболеваниях венозной системы нижних конечностей

Potential of artificial intelligence methods in diseases of the venous system of the lower extremities

https://orcid.org/0000-0001-7473-6692

Каторкин

С. Е.

Katorkin

S. Е.

Каторкин Сергей Евгеньевич, д.м.н., профессор, заведующий кафедрой и клиникой госпитальной хирургии

443099, Самара, ул. Чапаевская, д. 89

Sergei E. Katorkin, Dr. Sci. (Med.), Professor, Head of the Department and Clinic of Hospital Surgery

89, Chapaevskaya St., Samara, 443089

katorkinse@mail.ru

Самарский государственный медицинский университетРоссияSamara State Medical UniversityRussian Federation

2026

07062026

2311529

2026

Каторкин С.Е.

Katorkin S.Е.

Данная работа распространяется под лицензией Creative Commons Attribution 4.0.

This work is licensed under a Creative Commons Attribution 4.0 License.

https://www.a-surgeon.ru/jour/article/view/621

Применение новых методов искусственного интеллекта (ИИ) стремительно меняет облик современной медицины, предлагая передовые инструменты для диагностики и лечения. Целью обзора является картирование ключевых концепций и направлений исследований в области применения методов ИИ при диагностике и лечении венозных заболеваний нижних конечностей. Обзор области исследования представлен в соответствии с рекомендациями PRISMA ScR. Поиск проведен по электронным базам данных Medline/ Pub Med, Web of Science, Scopus, Embase, ResearchGate, Google Scholar и Cochrane Database of Systematic Reviews на предмет исследований, опубликованных по декабрь 2025 г. Исследования включались в обзор, если в них применялись методы ИИ в диагностике и клинической практике. Проанализировано 1 071 исследование. Применение методов ИИ при патологии венозной системы нижних конечностей стремительно развивается и демонстрирует большие возможности для повышения прецизионности диагностики, автоматизации рабочих процессов и совершенствования принятия клинических решений. Достигнутая точность алгоритмов ИИ превышала 90%, значительно снижая вариабельность между наблюдателями и обеспечивая единообразную интерпретацию, исключая операторозависимость. Внедрение ИИ ускоряло диагностические рабочие процессы, сократив более чем на 50% время анализа изображений. Однако большинство исследований основывались на внутренних наборах данных с ограниченной интерпретируемостью моделей и отсутствием внешней валидации. Клиническое внедрение и оценка результатов остаются недостаточно изученными. Методы ИИ представляют собой преобразующую инновацию, которая, повышая диагностическую точность, оптимизируя рабочие процессы и обеспечивая персонализированный подход, имеет значительный потенциал для улучшения результатов лечения венозной патологии нижних конечностей. Многообещающее будущее ИИ – в широком использовании для прогнозирования, разработке стратегий персонализированного лечения пациентов на основе индивидуальных профилей и создании масштабных многоцентровых массивов данных для повышения надежности и универсальности алгоритмов. Приоритет необходимо отдать внешней валидации, стандартизации и внедрению ИИ в реальную клиническую практику.

The use of new Artificial Intelligence (AI) methods is rapidly changing the face of modern medicine, offering advanced tools for diagnosis and treatment. The aim of this review is to map key concepts and research directions in the application of AI methods in the diagnosis and treatment oflower extremity venous diseases. This review is presented in accordance with the PRISMA ScR guidelines. A search was conducted in Medline/PubMed, Web of Science, Scopus, Embase, ResearchGate, Google Scholar, and the Cochrane Database of Systematic Reviews for studies published through December 2025. Studies were included in the review if they applied AI methods in diagnostics and clinical practice. A total of 1,071 studies were analyzed. The use of AI methods inlower extremity venous pathology is rapidly evolving and demonstrates significant potential for increasing diagnostic precision, automating workflows, and improving clinical decision making. The achieved accuracy of AI algorithms exceeded 90%, significantly reducing interobserver variability and ensuring consistent interpretation, eliminating operator dependency. The implementation of AI accelerated diagnostic workflows, reducing image analysis time by more than 50%. However, most studies relied on in-house datasets withlimited model interpretability and alack of external validation. Clinical implementation and outcome evaluation remain understudied. AI methods represent a transformative innovation that, by increasing diagnostic accuracy, streamlining workflows, and enabling a personalized approach, has significant potential to improve treatment outcomes for lower extremity venous pathology. AI has a promising future in its widespread use for prognostication, developing personalized treatment strategies for patients based on individual profiles, and creatinglarge-scale multicenter datasets to improve the reliability and versatility of algorithms. Priority should be given to external validation, standardization, and the implementation of AI in real-world clinical practice.

искусственный интеллектсверточные нейронные сетиглубокое машинное обучениедиагностикакомпьютерная помощьмедицинская диагностическая визуализацияультразвукмагнитно-резонансная томографияуправление электронными медицинскими картамихроническое заболевание венвенозный рефлюкстромбоз глубоких вен

artificial intelligenceconvolutional neural networksdeep machinelearningdiagnosticscomputer assistancemedical diagnostic imagingultrasoundmagnetic resonance imagingelectronic health record managementchronic venous diseasevenous refluxdeep vein thrombosis

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