Prediction of 24‐Hour Urinary Sodium Excretion Using Machine‐Learning Algorithms

Background Accurate quantification of sodium intake based on self‐reported dietary assessments has been a persistent challenge. We aimed to apply machine‐learning (ML) algorithms to predict 24‐hour urinary sodium excretion from self‐reported questionnaire information. Methods and Results We analyzed...

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Номзүйн дэлгэрэнгүй

Үндсэн зохиолчид:	Rikuta Hamaya, Molin Wang, Stephen P. Juraschek, Kenneth J. Mukamal, JoAnn E. Manson, Deirdre K. Tobias, Qi Sun, Gary C. Curhan, Walter C. Willett, Eric B. Rimm, Nancy R. Cook
Формат:	Artigo
Хэл сонгох:	Inglês
Хэвлэсэн:	Wiley 2024-05-01
Цуврал:	Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Нөхцлүүд:	dietary sodium food frequency questionnaire hypertension machine learning measurement error
Онлайн хандалт:	https://www.ahajournals.org/doi/10.1161/JAHA.123.034310
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!