[ACMMM 2025] TolerantECG: A Foundation Model for Imperfect Electrocardiogram

This repository contains the source code of paper TolerantECG: A Foundation Model for Imperfect Electrocardiogram

Data preprocessing

The data used in this work can be downloaded using the links below:

• MIMIC-IV-IV: https://physionet.org/content/mimic-iv-ecg/1.0/
• MIMIC-IV-ECG-Ext-ICD: https://physionet.org/content/mimic-iv-ecg-ext-icd-labels/1.0.1/
• MIT-BIH: https://www.physionet.org/content/mitdb/1.0.0/
• MIT-BIH Noise Stress Test: https://www.physionet.org/content/nstdb/1.0.0/
• PTB-XL: https://physionet.org/content/ptb-xl/1.0.3/

After downloading, please put them in the data folder as such:

data
└───mimic-iv-ecg
|   |   machine_measurements.csv
│   |   record_list.csv
│   └───files
│       ...
└───mit-bih
|   │   100.atr
|   │   100.dat
│       ...
└───mit-noise
|   │   bw.dat
|   │   em.dat
|   │   ma.dat
│       ...
└───ptb-xl
|   │   pltxl_database.csv
|   │   scp_statements.csv
│   └───records500
│       ...

Installation requirement

The necessary requirements can be installed using pip:

pip install -r requirements.txt

Create CFR database

python -m src.init_cfr

Training & fintuning

The training scripts are provided in the script folder. Or it can be simply run as followed:

• Pretraining with MIMIC-IV-ECG:

./script/train.sh

• Finetune with PTB-XL Super-diagnosis:

./script/finetune.sh

Please note to change some of the arguments in the .sh files for desire modification.