Russian Journal of Pediatric Surgery, Anesthesia and Intensive CareRussian Journal of Pediatric Surgery, Anesthesia and Intensive CareРоссийский вестник детской хирургии, анестезиологии и реаниматологии2219-40612587-6554Eco-Vector154710.17816/psaic1547ReviewsОбзорыReview ArticleArtificial intelligence systems in surgery: A review of opportunities, limitations, and prospectsСистемы искусственного интеллекта в хирургии: возможности, ограничения и перспективы. Обзор литературы手术中的人工智能系统：能力、局限和前景。 文献综述https://orcid.org/0000-0002-3459-88517075-7784KobrinskiiBoris A.КобринскийБорис АркадьевичKobrinskiiBoris A.
Russian Federation

PhD, Dr. Sci. (Med.), Professor, Honored Scientist of the Russian Federation; Head of the Department of Intelligent Decision Support System; Chairman of the Scientific Council of the Russian Association of Artificial Intelligence

д-р мед. наук, профессор, заслуженный деятель науки Российской Федерации; заведующий отделом систем интеллектуальной поддержки принятия решений; председатель Научного совета Российской ассоциации искусственного интеллекта

PhD, Dr. Sci. (Med.), Professor, Honored Scientist of the Russian Federation; Head of the Department of Intelligent Decision Support System; Chairman of the Scientific Council of the Russian Association of Artificial Intelligence

kba_05@mail.ruFederal Research Center «Computer Sciens and Control» Russian Academy of SciencesФедеральный исследовательский центр «Информатика и управление» Российской академии наукFederal Research Center «Computer Sciens and Control» Russian Academy of Sciences29092023201020231333854042008202318092023Copyright ©; 2023, Eco-VectorCopyright ©; 2023, Эко-ВекторCopyright ©; 2023,2023Eco-VectorЭко-Векторhttps://creativecommons.org/licenses/by-nc-nd/4.0https://rps-journal.ru/jour/article/view/1547

Artificial intelligence technologies are increasingly being applied in a variety of medical disciplines. After reviewing 278 publications from 1985 to 2023, 99 articles were selected from the databases elibrary, PubMed, Medline, WoS, Nature, Springer, and Wiley J Database to present the main approaches and a modern picture of the application of artificial intelligence methods and technologies in pediatric surgery and intensive care. The article examines many facets of artificial intelligence systems for medical uses, namely, computer decision support systems or supporting the surgeon throughout the surgical intervention procedure. Computer analysis of 3D visualization and 3D anatomical modeling of images obtained from computed tomography and magnetic resonance imaging investigations can be used to plan operations. Because of the possibilities of sufficiently accurate 3D models and methods for organs and pathological processes, various methodologies and software tools for preoperative planning and intraoperative support of surgical intervention have been developed. Computer (technical) vision analyzes high-quality medical images and interprets them in multimodal three-dimensional images for computer diagnoses and operations under visual control, including augmented reality methods. Robotic surgery involves manipulators, including remotely controlled ones, and intellectualized complexes that independently perform specific actions of the “second assistant surgeon”. In intensive care, artificial intelligence technologies are being investigated to merge data from bedside monitors and other information about patients’ conditions to identify critical situations and control mechanical ventilation. Simultaneously, several obstacles impede the adoption of artificial intelligence in surgery. The nature and standardization of the initial data required for their integration, taking into consideration atypical cases, the possibility of bias in the sample used, and the transparency of the decision-making process in machine learning models are examples. The explanation of solutions presented in machine learning models and the transition to full-fledged validation of the systems being built define the prospects for developing and using artificial intelligence systems.

В настоящее время системы искусственного интеллекта находят все более широкое применение в различных областях медицины. В результате анализа 278 публикаций за 1985–2023 гг. в базах данных e-Library, PubMed, Medline, WoS, Nature, Springer, Wiley J Database отобрано 99 статей, которые позволили представить основные подходы и современную картину применения методов и технологий искусственного интеллекта в детской хирургии и интенсивной терапии. В статье рассматриваются различные аспекты систем искусственного интеллекта медицинского назначения, которые в основном являются системами компьютерной поддержки принятия врачебных решений или ассистирующими хирургу в процессе оперативных вмешательств. Операции могут планироваться с использованием компьютерного анализа 3D-визуализации, 3D-анатомического моделирования изображений, получаемых при компьютерной томографии и магниторезонансной томографии. Возможности достаточно точных 3D-моделей и методов визуализации органов и патологических процессов позволили разработать ряд методик и программных средств для предоперационного планирования и интраоперационного сопровождения хирургического вмешательства. Компьютерное (техническое) зрение обеспечивает высокое качество анализа медицинских изображений, их интерпретацию в мультимодальных трехмерных изображениях для компьютерной диагностики и в процессе операций под визуальным контролем, включая методы дополненной реальности. Роботизированная хирургия включает манипуляторы, в том числе дистанционно управляемые, и интеллектуализированные комплексы, участвующие в проведении операции, автономно осуществляя определенные действия «второго ассистирующего хирурга». Технологии искусственного интеллекта в интенсивной терапии рассматриваются в аспекте сочетания данных с прикроватных мониторов и другой информации о состоянии пациентов для выявления критических ситуаций и контроля искусственной вентиляции легких. В то же время имеется ряд факторов, сдерживающих применение искусственного интеллекта в хирургии. Это характер и стандартизация исходных данных, необходимая для их объединения, учет атипичных случаев, риск смещения используемой выборки, прозрачность процесса принятия решений в моделях машинного обучения. Перспективы развития и применения систем искусственного интеллекта определяются решением объяснимости решений, предлагаемых в моделях машинного обучения, и переходом к полноценной валидации создаваемых систем.

如今，人工智能系统越来越多地应用于医学的各个领域。通过对eLibrary、PubMed、Medline、WoS、 Nature、Springer、Wiley J Database中1985-2023年间的278篇出版物进行的分析，选出了99篇文章。这些文章介绍人工智能方法和技术在儿科手术和重症监护中应用的主要方法和现状。本文涉及医用人工智能系统的各种各样方面。这些系统主要是计算机医疗决策支持系统或外科手术干预过程中的外科医生助手。可以通过计算机分析三维成像、计算机断层扫描和磁共振成像的三维解剖建模来规划手术。有了足够精确的三维模型以及器官和病理过程的可视化方法，就可以开发出一系列用于术前规划和术中支持手术干预的技术和软件工具。计算机（技术）视觉允许对医学图像进行高质量的分析，在多模态三维图像中及在视觉控制下的手术过程中对其进行解读（以用于计算机诊断）和，包括增强现实方法。机器人手术涉及机械手（包括遥控机械手）和智能综合体。这些综合体参与手术，并自主执行“第二辅助外科医生”的某些操作。重症监护领域的人工智能技术正在考虑将床边监护仪的数据和其他病人信息结合起来，以识别危急情况并控制肺通气支持。与此同时， 人工智能在外科手术中的应用还受到一些因素的制约。这些因素包括：组合所需的初始数据的性质和标准化、对非典型病例的考虑、所用样本存在偏差的风险以及机器学习模型决策过程的透明度。人工智能系统的开发和应用前景取决于机器学习模型中提出的决策可解释性，以及向所创建系统的全面验证。

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