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

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

Abstract 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 fibrill...

Full description

Bibliographic Details
Main Authors: Giovanni Baj, Ilaria Gandin, Arjuna Scagnetto, Luca Bortolussi, Chiara Cappelletto, Andrea Di Lenarda, Giulia Barbati
Format: Article
Language:English
Published: BMC 2023-07-01
Series:BMC Medical Research Methodology
Subjects:
Atrial fibrillation
Prediction
Calibration
Machine learning
Deep learning
Online Access:https://doi.org/10.1186/s12874-023-01989-3

Internet

https://doi.org/10.1186/s12874-023-01989-3

Similar Items