Технологии искусственного интеллекта в эндоскопии пищеварительной системы: состояние проблемы и перспективы (обзор литературы)

Представлен комплексный анализ современного состояния и перспектив применения технологий искусственного интеллекта (ИИ) в эндоскопии пищеварительной системы. Исследование охватывает основные направления внедрения ИИ в эндоскопическую практику, включая системы компьютерного зрения CADe и CADx, методы машинного обучения и алгоритмы глубокого обучения. Рассматриваются особенности эндоскопических процедур, влияющие на эффективность применения ИИ-технологий: подготовка пациента, качество визуализации в зависимости от навыков эндоскописта, мультимодальность современных эндоскопических методов. Результаты демонстрируют активное развитие ИИ-технологий в эндоскопии, особенно в области выявления патологических изменений желудочно-кишечного тракта. Ключевые направления применения ИИ включают онкопоиск, диагностику Helicobacter pylori, оценку воспалительных заболеваний и контроль качества исследований. Анализ показывает, что несмотря на значительные успехи в разработке ИИ-систем для эндоскопии, их внедрение ограничено рядом факторов, включая зависимость от оператора и сложности стандартизации. В ближайшем будущем для обучения ИИ-моделей будут внедрятся новые подходы, включая рекурентные нейронные сети и мультимодальные ИИ-системы, объединяющие визуальные данные с другой информацией о пациенте.

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