急诊科
医学
电子健康档案
健康档案
心力衰竭
利钠肽
医疗急救
深度学习
模棱两可
急诊医学
重症监护医学
内科学
人工智能
医疗保健
计算机科学
护理部
经济
经济增长
程序设计语言
作者
Chih‐Kuo Lee,Ting‐Li Chen,Jeng-En Wu,Min‐Tsun Liao,Chiehhung Wang,Weichung Wang,Cheng‐Ying Chou
标识
DOI:10.1016/j.cmpb.2024.108357
摘要
Ambiguity in diagnosing acute heart failure (AHF) leads to inappropriate treatment and potential side effects of rescue medications. To address this issue, this study aimed to use multimodality deep learning models combining chest X-ray (CXR) and electronic health record (EHR) data to screen patients with abnormal N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels in emergency departments.
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