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Возможности и ограничения искусственного интеллекта во флебологии: результаты систематического обзора литературы с метаанализом

Возможности и ограничения искусственного интеллекта во флебологии: результаты систематического обзора литературы с метаанализом

Авторы:
Дамир Александрович Аверин,
Кирилл Викторович Лобастов,
Леонид Александрович Лаберко

Журнал: Флебология. 2026;20(3):220-248.

DOI: 10.17116/flebo202620031220

Прочитано: 69 раз

Резюме

ЦЕЛЬ ИССЛЕДОВАНИЯ

Количественным образом оценить эффективность технологий на основе искусственного интеллекта (ИИ) при заболеваниях венозной системы.

МАТЕРИАЛ И МЕТОДЫ

Проведен систематический поиск литературы в базах данных PubMed, Cochrane Library и Google Scholar. В анализ включали оригинальные исследования, использовавшие ИИ-модели при венозной патологии, включая венозные тромбоэмболические осложнения (ВТЭО) и хронические заболевания вен (ХЗВ). Критериями оценки в исследованиях служили прогностическая и диагностическая эффективность, обобщенные с помощью модели случайных эффектов.

РЕЗУЛЬТАТЫ

Из оцененных 606 работ в анализ включено 100 исследований по вопросам прогнозирования (76 публикаций) и диагностики (24) ВТЭО (86) и ХЗВ (14). Для диагностических моделей ВТЭО и ХЗВ обобщенные точность, чувствительность и специфичность при внутренней валидации составили: 0,93 (95% ДИ 0,87—0,96) и 0,98 (95% ДИ 0,91—0,99); 0,89 (95% ДИ 0,81—0,96) и 0,89 (95% ДИ 0,80—0,95); 0,93 (95% ДИ 0,87—0,98) и 0,94 (95% ДИ 0,67—0,99) соответственно. Для предсказательных моделей ВТЭО обобщенные точность, чувствительность, специфичность, прецизионность и значения площади под кривой ROC (ППК) по результатам внутренней валидации составили 0,85 (95% ДИ 0,83—0,88), 0,78 (95% ДИ 0,72—0,85), 0,86 (95% ДИ 0,80—0,92), 0,60 (95% ДИ 0,45—0,74) и 0,86 (ДИ 95% 0,84—0,88) соответственно. Для предсказательных моделей ХЗВ обобщенная ППК составила 0,88 (ДИ 95% 0,82—0,95). Внешняя валидация была выполнена только в 23% случаев, а полученные метрики уступали результатам внутренней валидации.

ЗАКЛЮЧЕНИЕ

Технологии на основе ИИ демонстрируют высокую диагностическую и умеренную прогностическую эффективность при патологии венозной системы, однако требуются дальнейшие исследования с внешней валидацией для оценки внедрения в клиническую практику.

Ключевые слова

  • венозные тромбоэмболические осложнения
  • хронические заболевания вен
  • искусственный интеллект
  • прогнозирование
  • диагностика

Дата поступления: 05.06.2026

Дата принятия в печать: 24.06.2026

Дата публикации: 22.09.2026

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