https://github.com/smilelab-fl/fedcvd
The First Real-World Federated Learning Benchmark on Cardiovascular Disease Data
https://github.com/smilelab-fl/fedcvd
Last synced: about 2 months ago
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The First Real-World Federated Learning Benchmark on Cardiovascular Disease Data
- Host: GitHub
- URL: https://github.com/smilelab-fl/fedcvd
- Owner: SMILELab-FL
- Created: 2024-06-06T05:08:02.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-02-20T08:01:41.000Z (3 months ago)
- Last Synced: 2025-02-20T09:22:27.747Z (3 months ago)
- Language: Python
- Size: 2.43 MB
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# FedCVD
The First Real-World Federated Learning Benchmark on Cardiovascular Disease Data
## Framework
## Installation
### Directory Structure
We recommend the user to use `FedCVD` following the directory structure below:
data: store the raw data and preprocessed data for each client;
code: use `FedCVD` in this directory;
output: store results and log files。
The directory structure is shown below:
```grapha
├── workspace
│ └── data
│ │ ├── ECG
│ │ │ ├── raw
│ │ │ │ ├── SPH
│ │ │ │ ├── PTB
│ │ │ │ ├── SXPH
│ │ │ │ ├── G12EC
│ │ │ ├── preprocessed
│ │ │ │ ├── client1
│ │ │ │ ├── client2
│ │ │ │ ├── client3
│ │ │ │ ├── client4
│ │ ├── ECHO
│ │ │ ├── raw
│ │ │ │ ├── CAMUS
│ │ │ │ ├── ECHONET
│ │ │ │ ├── HMCQU
│ │ │ ├── preprocessed
│ │ │ │ ├── client1
│ │ │ │ ├── client2
│ │ │ │ ├── client3
│ ├── output
│ └── code
│ └── FedCVD
```
You can run scripts below to create the directory structure:
```bash
mkdir workspace
cd workspace
mkdir data code output
cd data
mkdir -p ECG/raw ECG/preprocessed ECHO/raw ECHO/preprocessed
cd ECG/raw
mkdir SPH PTB SXPH G12EC
cd ../../ECHO/raw
mkdir CAMUS ECHONET HMCQU
cd ../../../
cd code
```
### Data Downloading
Datasets for **Fed-ECG** can be downloaded from the URLs below:
- client1: [SPH](https://springernature.figshare.com/collections/A_large-scale_multi-label_12-lead_electrocardiogram_database_with_standardized_diagnostic_statements/5779802/1)
- client2: [PTB-XL](https://physionet.org/content/ptb-xl/1.0.3/)
- client3: [SXPH](https://physionet.org/content/ecg-arrhythmia/1.0.0/)
- client4: [G12EC](https://physionet.org/content/challenge-2020/1.0.2/)
Datasets for **Fed-ECHO** can be downloaded from the URLs below:
- client1: [CAMUS](https://humanheart-project.creatis.insa-lyon.fr/database/#collection/6373703d73e9f0047faa1bc8)
- client2: [ECHONET-DYNAMIC](https://echonet.github.io/dynamic/index.html#access)
- client3: [HMC-QU](https://www.kaggle.com/datasets/aysendegerli/hmcqu-dataset/data)
Note that a Stanford AIMI account is required to access the ECHONET-DYNAMIC dataset and a Kaggle account is required to access the HMC-QU dataset.
### Data Preprocessing
Make sure the data is stored in the correct directory structure. The reference structure is shown below:
- **SPH** directory must contain the following files or directories:
```grapha
├── SPH
│ ├── ...
│ ├── metadata.csv
│ ├── records
│ │ ├── A00001.h5
│ │ ├── ...
│ │ └── A25770.h5
```
- **PTB** directory must contain the following files or directories:
```grapha
├── PTB
│ ├── ...
│ ├── ptbxl_database.csv
│ ├── records500
│ │ ├── 00000
│ │ │ ├── 00001_hr.dat
│ │ │ ├── 00001_hr.hea
│ │ │ └── ...
│ │ ├── ...
│ │ └── 21000
```
- **SXPH** directory must contain the following files or directories:
```grapha
├── SXPH
│ ├── ...
│ ├── WFDBRecords
│ │ ├── 01
│ │ │ ├── 010
│ │ │ │ ├── JS00001.hea
│ │ │ │ ├── JS00001.mat
│ │ │ │ └── ...
│ │ │ ├── ...
│ │ ├── ...
│ │ └── 46
```
- **G12EC** directory must contain the following files or directories:
```grapha
├── G12EC
│ ├── g1
│ │ ├── E00001.hea
│ │ ├── E00001.mat
│ │ └── ...
│ ├── ...
│ └── g11
```
- **CAMUS** directory must contain the following files or directories:
```grapha
├── CAMUS
│ ├── training
│ │ ├── patient0001
│ │ ├── ...
│ │ └── patient0450
│ ├── testing
│ │ ├── patient0001
│ │ ├── ...
│ │ └── patient0050
```
- **ECHONET** directory must contain the following files or directories:
```grapha
├── ECHONET
│ ├── ...
│ ├── FileList.csv
│ ├── VolumeTracings.csv
│ ├── Videos
│ │ ├── 0X1A0A263B22CCD966.avi
│ │ └── ...
```
- **HMCQU** directory must contain the following files or directories:
```grapha
├── HMCQU
│ ├── ...
│ ├── A4C.xlsx
│ ├── HMC-QU
│ │ ├── A4C
│ │ │ ├── ES0001 _4CH_1.avi
│ │ │ └── ...
│ ├── LV Ground-truth Segmentation Masks
│ │ ├── Mask_ES0001 _4CH_1.mat
│ │ └── ...
```
After downloading the data, you can run the following scripts to preprocess and split the data:
```bash
cd code/FedCVD/
bash scripts/preprocess/preprocess.sh
bash scripts/preprocess/split.sh
```
### Environment Setup
You can use the following scripts to set up the environment:
```bash
cd code/FedCVD/
conda create -n fedcvd_env python=3.11 -y
conda activate fedcvd_env
pip install -r requirements.txt
```
## Usage
You can run the scripts in the `code/FedCVD/scripts` directory to reproduce our experiments.