2226-5988 2686-6749 Клиническая и экспериментальная морфология Clinical and Experimental Morphology ООО "Группа МДВ" 10.31088/CEM2024.13.3.5-15 Исследование патологии желудка с использованием методов искусственного интеллекта для анализа данных микроскопии Studying gastric pathologies using artificial intelligence to analyze microscopy data Волкова Лариса Владимировна Волкова Лариса Владимировна Volkova Larisa V. volkovalr16@gmail.com 0000-0003-0938-8577 Батищев Александр Витальевич Батищев Александр Витальевич Batishchev Alexander V. cem.journal@mail.ru 0000-0003-4872-0608 Михалева Людмила Михайловна Михалева Людмила Михайловна Mikhaleva Liudmila M. cem.journal@mail.ru 0000-0003-2052-914X НОЧУ ВО Московский финансово-промышленный университет «Синергия» Moscow Financial and Industrial University “Synergy” Научно-исследовательский институт морфологии человека имени академика А.П. Авцына ФГБНУ «Российский научный центр хирургии имени академика Б.В. Петровского» Avtsyn Research Institute of Human Morphology of FSBSI “Petrovsky National Research Centre of Surgery” 01 09 2024 13 3 5 15 28 02 2024 01 04 2024 11 03 2024

Рак желудка (РЖ) – онкологическое заболевание, характеризующееся высокой заболеваемостью и смертностью, нередко диагностируемое на поздних стадиях. В связи с этим проблема ранней диагностики предопухолевой патологии и карцином желудка является крайне актуальной. Исследования, направленные на совершенствование диагностики, выявление объективных предиктивных и прогностических критериев, имеют не только важнейшее практическое значение, они позволяют уточнить этапы желудочного канцерогенеза, верифицировать значимость отдельных патологических изменений в слизистой оболочке желудка. В последние годы для решения практических и теоретических задач при оценке предраковых и неопластических процессов в эпителии желудка применяются как традиционные морфологические, иммуногистохимические, молекулярно-генетические методы, так и методы интеллектуального анализа данных. В работе приводится обзор научных публикаций, освещающих проблему использования методов искусственного интеллекта, которые представлены в базе PubMed за 2017–2024 годы. Проведена оценка возможностей и перспектив использования искусственного интеллекта при изучении фоновых, предраковых и неопластических процессов в эпителии желудка, на основе данных, полученных в основном с помощью традиционных методов световой микроскопии.

Gastric cancer (GC) has high morbidity and mortality and is often diagnosed at late stages. Thus, early diagnosis of precancerous pathologies and gastric carcinomas is highly relevant. The studies aimed at improving the diagnosis and identifying objective predictive and prognostic criteria are of great practical significance and make it possible to clarify the stages of gastric carcinogenesis, verify the significance of individual pathological changes in the gastric mucosa. In recent years, researchers have used both traditional and modern methods to solve practical and theoretical problems in assessing precancerous and neoplastic processes in the gastric epithelium. The former group includes morphological and immunohistochemical methods as well as molecular genetic techniques. The latter group encompasses data mining and AI. The paper provides an overview of scientific publications covering the problem of using artificial intelligence methods, which are presented in the PubMed database for 2017–2024. We assessed future possible uses of AI when studying background, precancerous, and neoplastic processes in the gastric epithelium. The data obtained mainly with traditional methods of light microscopy were used.

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