医学
阻塞性睡眠呼吸暂停
心脏病学
睡眠呼吸暂停
内科学
纵向数据
数据挖掘
计算机科学
作者
Yi Yang,Haibing Jiang,Haitao Yang,Xian‐Geng Hou,Ting-Ting Wu,Ying Pan,Xiang Xie
标识
DOI:10.31083/j.rcm2507258
摘要
It is crucial to accurately predict the disease progression of systemic arterial hypertension in order to determine the most effective therapeutic strategy. To achieve this, we have employed a multimodal data-integration approach to predict the longitudinal progression of new-onset systemic arterial hypertension patients with suspected obstructive sleep apnea (OSA) at the individual level.
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