СРАВНИТЕЛЬНАЯ ОЦЕНКА ПРОГНОЗИРОВАНИЯ РИСКА СЕРДЕЧНО-СОСУДИСТЫХ ЗАБОЛЕВАНИЙ У ЛЮДЕЙ С САХАРНЫМ ДИАБЕТОМ 2 ТИПА: ПОКАЗАТЕЛИ, ГЕОГРАФИЯ, МОДЕЛИ ИСКУСТВЕННОГО ИНТЕЛЛЕКТА
Ключевые слова:
сердечно-сосудистые заболевания, сахарный диабет, прогноз, машинное обучение, искусственный интеллектАннотация
Сахарный диабет 2 типа (СД 2) является распространенным хроническим заболеванием, причиной которого является нарушение выделения инсулина. Из-за осложнений СД 2, исходы этого заболевания приводят к тяжелым сердечно-сосудистым заболеваниям (ССЗ). Сегодня, учитывая постоянное увеличение числа пациентов с СД, необходимо найти новые инструменты для выявления пациентов с высоким риском сердечно-сосудистых осложнений. В этом процессе есть два ключевых момента: набор показателей и математические модели прогнозирования. Поэтому статья дает ответы на три вопроса: 1. Есть ли существенная разница в наборах признаков из разных исследованиях (цель, география, этнос)? 2. Есть ли необходимость создавать собственные наборы признаков, а не использовать известные прогнозные индикаторы? 3. Есть ли эффект применения методов глубокого обучения в сравнении с традиционными методами (статистика и машинное обучение)? Ответы на эти вопросы основаны на анализе обширных новейших публикаций по исследуемой проблеме.
Библиографические ссылки
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