Fig. 1: Flowchart of the study design showing the sample sizes for different experimental splits. | npj Digital Medicine

Fig. 1: Flowchart of the study design showing the sample sizes for different experimental splits.

From: Development and validation of machine learning algorithms based on electrocardiograms for cardiovascular diagnoses at the population level

Fig. 1

We divided the entire ECG dataset, allocating 60% for model development (including fivefold internal cross-validation for training and fine-tuning) and setting aside 40% as a holdout set for final validation. For evaluation, we assessed our models using two approaches: first, exclusively on the first ECGs from each episode captured during an ED visit or hospitalization, reflecting the intended point-of-care deployment; second, on all ECGs from the holdout set. Additionally, we evaluated our models’ performance within specific patient subgroups categorized by sex and the presence of cardiac pacing or ventricular assist devices.

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