Биометрические данные и методы машинного обучения в диагностике и мониторинге нейродегенеративных заболеваний: обзор

Биометрические данные и методы машинного обучения в диагностике и мониторинге нейродегенеративных заболеваний: обзор

Автор: Ходашинский Илья Александрович, Сарин Константин Сергеевич, Бардамова Марина Борисовна, Светлаков Михаил Олегович, Слзкин Артем Олегович, Корышев Николай Павлович

Журнал: Компьютерная оптика @computer-optics

Рубрика: Численные методы и анализ данных

Статья в выпуске: 6 т.46, 2022 года.

Бесплатный доступ

Представлен обзор неинвазивных биометрических методов выявления и прогнозирования развития нейродегенеративных заболеваний. Дан анализ различных модальностей, используемых для диагностики и мониторинга. Рассмотрены такие модальности, как рукописные данные, электроэнцефалограмма, речь, походка, движение глаз, а также использование композиций данных модальностей. Проведен подробный анализ современных методов и систем принятия решений, основанных на машинном обучении. Представлены наборы данных, методы предобработки, модели машинного обучения, оценки точности при диагностике заболеваний. В заключении рассмотрены текущие открытые проблемы и будущие перспективы исследований в данном направлении.

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Неинвазивные методы диагностики, нейродегенеративные заболевания, обработка биометрических сигналов, машинное обучение

Короткий адрес: https://sciup.org/140296246

IDR: 140296246   |   DOI: 10.18287/2412-6179-CO-1134

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