Sources & Attributions

Open-data and openly-licensed sources used in CardioQFlow content. License terms link directly to the original. CardioQFlow is itself a copyrighted work; everything below documents the third-party data we incorporate under the licenses cited.

Electrocardiogram Signal Data

PTB-XL — Large Publicly Available Electrocardiography Dataset

Version 1.0.3 CC BY 4.0 21,799 records

Twelve-lead clinical resting ECGs derived under IRB approval at the Physikalisch-Technische Bundesanstalt (Germany), de-identified, with expert-adjudicated SCP-ECG diagnostic statements. Signals are licensed under the Creative Commons Attribution 4.0 International license. CardioQFlow renders selected records as 12-lead and rhythm-strip teaching figures, attributing each rendered image inline.

Wagner P, Strodthoff N, Bousseljot RD, Samek W, Schaeffter T. PTB-XL, a large publicly available electrocardiography dataset (version 1.0.3). PhysioNet. 2022. https://physionet.org/content/ptb-xl/1.0.3/
Wagner P, Strodthoff N, Bousseljot RD, Kreiseler D, Lunze FI, Samek W, Schaeffter T. PTB-XL, a large publicly available electrocardiography dataset. Sci Data. 2020;7:154. https://doi.org/10.1038/s41597-020-0495-6

MIT-BIH Malignant Ventricular Arrhythmia Database

Version 1.0.0 ODC-By 1.0 22 records

Half-hour ambulatory ECG recordings of patients who experienced sustained ventricular tachycardia, ventricular flutter, and ventricular fibrillation. Used for our sustained-VT teaching figures where PTB-XL's resting clinical cohort lacks the necessary rhythm. Licensed under the Open Data Commons Attribution License v1.0 — same commercial terms as the parent CC BY family, with attribution required.

Greenwald SD. The development and analysis of a ventricular fibrillation detector. M.S. thesis, MIT Dept. of Electrical Engineering and Computer Science, 1986. PhysioNet: https://physionet.org/content/vfdb/1.0.0/
Goldberger AL, Amaral LAN, Glass L, et al. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation. 2000;101(23):e215-e220. https://doi.org/10.1161/01.CIR.101.23.e215

Synthetic ECG Signals (CardioQFlow editorial pipeline)

In-house No third-party rights

For pathology patterns not adequately represented in the open ECG datasets (acute pericarditis ST elevation patterns, TCA-overdose wide-QRS morphology, certain composite features), CardioQFlow renders stylized teaching figures using a synthetic ECG generator. The generator combines the open-source neurokit2 ECGSYN model (McSharry 2003 dynamical model, MIT license) with editorial post-processing to highlight the relevant teaching feature. These synthetic figures are clearly labeled "Synthetic ECG · CardioQFlow editorial pipeline" inline. No real patient data is used.

McSharry PE, Clifford GD, Tarassenko L, Smith LA. A dynamical model for generating synthetic electrocardiogram signals. IEEE Trans Biomed Eng. 2003;50(3):289-294. https://doi.org/10.1109/TBME.2003.808805

Cardiology Guidelines & Society Statements

CardioQFlow question explanations cite published clinical practice guidelines from the American College of Cardiology, American Heart Association, European Society of Cardiology, Heart Rhythm Society, and other professional societies. Each citation includes the publication, year, and DOI for direct verification. CardioQFlow does not reproduce guideline text or figures; it cites and paraphrases under fair-use principles for educational commentary.

Clinical Imaging

All clinical-style imaging (echocardiography, CMR, CCTA, SPECT, PET, angiography, histology) used in CardioQFlow figures is created originally by the editorial team using SVG, Python rendering pipelines, or generative tooling. No copyrighted clinical images are reproduced.

Brand & Iconography

CardioQFlow's logo, favicon, color palette, and UI iconography are original works. The brand red (#ef4444) is a palette token; no third-party brand assets are used.

Reporting an Attribution Issue

If you believe a source has been inadequately attributed, or if you hold rights to material you believe is incorporated without permission, please reach us via the in-app Contact Support form or email sarotoniin@gmail.com.