Predictive modeling for acute kidney injury after percutaneous coronary intervention in patients with acute coronary syndrome: a machine learning approach

Abstract Background Acute kidney injury (AKI) is one of the preventable complications of percutaneous coronary intervention (PCI). This study aimed to develop machine learning (ML) models to predict AKI after PCI in patients with acute coronary syndrome (ACS). Methods This study was conducted at Teh...

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Detalhes bibliográficos

Principais autores:	Amir Hossein Behnoush, M. Moein Shariatnia, Amirmohammad Khalaji, Mahsa Asadi, Alireza Yaghoobi, Malihe Rezaee, Hamidreza Soleimani, Ali Sheikhy, Afsaneh Aein, Somayeh Yadangi, Yaser Jenab, Farzad Masoudkabir, Mehdi Mehrani, Mina Iskander, Kaveh Hosseini
Formato:	Artigo
Idioma:	Inglês
Publicado em:	BMC 2024-01-01
coleção:	European Journal of Medical Research
Assuntos:	Acute coronary syndrome Percutaneous coronary intervention Acute kidney injury Machine learning Prediction
Acesso em linha:	https://doi.org/10.1186/s40001-024-01675-0
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