A novel, machine-learning model for prediction of short-term ASCVD risk over 90 and 365 days

• Автори: Tomer Gazit (Автор), Hanan Mann (Автор), Shiri Gaber (Автор), Pavel Adamenko (Автор), Granit Pariente (Автор), Liron Volsky (Автор), Amir Dolev (Автор), Helena Lyson (Автор), Eyal Zimlichman (Автор), Jay A. Pandit (Автор), Edo Paz (Автор)
• Формат: Книга
• Опубліковано: Frontiers Media S.A., 2024-11-01T00:00:00Z.
• Предмети: article
• Онлайн доступ: Connect to this object online.

BackgroundCurrent atherosclerotic cardiovascular disease (ASCVD) risk assessment tools like the Pooled Cohort Equations (PCEs) and PREVENT™ scores offer long-term predictions but may not effectively drive behavior change. Short-term risk predictions using mobile health (mHealth) data and electronic...