Unsupervised machine learning identifies symptoms of indigestion as a predictor of acute decompensation and adverse cardiac events in patients with heart failure presenting to the emergency department.
Unsupervised machine learning identifies symptoms of indigestion as a predictor of acute decompensation and adverse cardiac events in patients with heart failure presenting to the emergency department.
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无监督机器学习可识别消化不良症状,作为急诊室心力衰竭患者急性代偿失调和不良心脏事件的预测因子。
DOI:
10.1016/j.hrtlng.2023.05.012
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发表时间:
2023
期刊:
影响因子:
--
通讯作者:
Al-Zaiti,SalahS
中科院分区:
文献类型:
--
作者:
Kraevsky-Phillips,Karina;Sereika,SusanM;Bouzid,Zeineb;Hickey,Gavin;Callaway,CliftonW;Saba,Samir;Martin-Gill,Christian;Al-Zaiti,SalahS
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影响因子:
2.8
作者:
Nieminen, MS;Harjola, VP
通讯作者:
Harjola, VP
影响因子:
4
作者:
Bosco E;Hsueh L;McConeghy KW;Gravenstein S;Saade E
通讯作者:
Saade E
影响因子:
3.5
作者:
Gil Marcus;S. Shimony;G. Y. Stein;S. Matezky;Z. Iakobishvili;S. Minha;S. Fuchs
通讯作者:
S. Fuchs
DOI:
10.1016/j.hrtlng.2018.03.013
发表时间:
2018
期刊:
Heart & Lung: The Journal of Acute & Critical Care
影响因子:
--
作者:
C. Schumacher;L. Hussey;Vincent Hall
通讯作者:
Vincent Hall
DOI:
10.1186/cc4926
发表时间:
2006
期刊:
Critical care (London, England)
影响因子:
--
作者:
Ray P;Birolleau S;Lefort Y;Becquemin MH;Beigelman C;Isnard R;Teixeira A;Arthaud M;Riou B;Boddaert J
通讯作者:
Boddaert J