Machine learning–based biomarker profile derived from 4210 serially measured proteins predicts clinical outcome of patients with heart failure

AIMS: Risk assessment tools are needed for timely identification of patients with heart failure (HF) with reduced ejection fraction (HFrEF) who are at high risk of adverse events. In this study, we aim to derive a small set out of 4210 repeatedly measured proteins, which, along with clinical charact...

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Detalles Bibliográficos
Autores principales: de Bakker, Marie, Petersen, Teun B, Rueten-Budde, Anja J, Akkerhuis, K Martijn, Umans, Victor A, Brugts, Jasper J, Germans, Tjeerd, Reinders, Marcel J T, Katsikis, Peter D, van der Spek, Peter J, Ostroff, Rachel, She, Ruicong, Lanfear, David, Asselbergs, Folkert W, Boersma, Eric, Rizopoulos, Dimitris, Kardys, Isabella
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10689916/
https://www.ncbi.nlm.nih.gov/pubmed/38045440
http://dx.doi.org/10.1093/ehjdh/ztad056

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10689916/
https://www.ncbi.nlm.nih.gov/pubmed/38045440
http://dx.doi.org/10.1093/ehjdh/ztad056

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