Comparison of discrimination and calibration performance of ECG-based machine learning models for prediction of new-onset atrial fibrillation

BACKGROUND: Machine learning (ML) methods to build prediction models starting from electrocardiogram (ECG) signals are an emerging research field. The aim of the present study is to investigate the performances of two ML approaches based on ECGs for the prediction of new-onset atrial fibrillation (A...

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Detalles Bibliográficos
Autores principales: Baj, Giovanni, Gandin, Ilaria, Scagnetto, Arjuna, Bortolussi, Luca, Cappelletto, Chiara, Di Lenarda, Andrea, Barbati, Giulia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10363301/
https://www.ncbi.nlm.nih.gov/pubmed/37481514
http://dx.doi.org/10.1186/s12874-023-01989-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10363301/
https://www.ncbi.nlm.nih.gov/pubmed/37481514
http://dx.doi.org/10.1186/s12874-023-01989-3

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