Искусственный интеллект в лучевой диагностике: современное состояние, доказательная база и перспективы внедрения

Цель исследования. Систематизировать современные направления применения искусственного интеллекта (ИИ) в лучевой диагностике, проанализировать доказательную базу, клиническую эффективность и ограничения реального внедрения, а также оценить регуляторные, этические и организационно-экономические факторы.

Материалы и методы. Проведен описательный аналитический обзор публикаций за период 2020–2026 гг., индексируемых в базах PubMed/MEDLINE, РИНЦ, с анализом основных направлений применения ИИ в радиологии.

Результаты. В обзоре представлен анализ современного состояния применения технологий ИИ в лучевой диагностике. Рассмотрены основные направления клинического использования ИИ-систем: выявление и классификация патологических образований, количественная оценка очаговых поражений, реконструкция медицинских изображений и формирование структурированных заключений. Проанализирована доказательная база эффективности ИИ-решений с учетом результатов внешней валидации. Обсуждены регуляторные требования, этические проблемы и организационные аспекты внедрения ИИ. Особое внимание уделено ограничениям существующих исследований и перспективам развития данного направления.
Заключение. ИИ-системы демонстрируют значительный потенциал для повышения качества и эффективности лучевой диагностики, однако их клиническая ценность определяется не только показателями точности, но и способностью надежно работать в условиях реальной практики и соответствием регуляторным требованиям. 

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