Phenogrouping heart failure with preserved or mildly reduced ejection fraction using electronic health record data

Abstract Background Heart failure (HF) with preserved or mildly reduced ejection fraction includes a heterogenous group of patients. Reclassification into distinct phenogroups to enable targeted interventions is a priority. This study aimed to identify distinct phenogroups, and compare phenogroup ch...

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Hlavní autoři:	Fardad Soltani, David A. Jenkins, Amit Kaura, Joshua Bradley, Nicholas Black, John P. Farrant, Simon G. Williams, Abdulrahim Mulla, Benjamin Glampson, Jim Davies, Dimitri Papadimitriou, Kerrie Woods, Anoop D. Shah, Mark R. Thursz, Bryan Williams, Folkert W. Asselbergs, Erik K. Mayer, Christopher Herbert, Stuart Grant, Nick Curzen, Iain Squire, Thomas Johnson, Kevin O’Gallagher, Ajay M. Shah, Divaka Perera, Rajesh Kharbanda, Riyaz S. Patel, Keith M. Channon, Richard Lee, Niels Peek, Jamil Mayet, Christopher A. Miller
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	BMC 2024-07-01
Edice:	BMC Cardiovascular Disorders
Témata:	Heart failure with preserved or mildly reduced ejection fraction Machine learning Electronic health records
On-line přístup:	https://doi.org/10.1186/s12872-024-03987-9
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