ECG-aging
importedsoftware/ecg-aging
Source code repository for the study: "Uncovering ECG Changes during Healthy Aging using Explainable AI"
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- AI4HealthUOL
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/AI4HealthUOL/ECG-aging
- Documentation
- unknown
- Tags
- ecg · ecg-classification · healthy-aging
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- automatic-ecg-diagnosisecg · ecg-classification
Scripts and modules for training and testing neural network for ECG automatic classification. Companion code to the paper "Automatic diagnosis of the 12-lead ECG using a deep neural network".
- awecgecg · ecg-classification
Flutter ECG application to Windows and Android.
- CardioLabecg · ecg-classification
This is the official repository for CardioLab. A machine and deep learning framework for the estimation and monitoring of laboratory abnormalities throught ECG data.
- dot-res-lstmecg · ecg-classification
Classification of ECG signals by dot Residual LSTM Network for anomaly detection
- ECG-GANecg · ecg-classification
Synthesize plausible ECG signals via Generative adversarial networks
- ECG-Multi-Label-Classification-Using-Multi-Modelecg · ecg-classification
In this project, we will perform 12-lead ECG Multi-label Classification. Specifically, we will design a multi-model utilizing the characteristics of diagnoses from the Shaoxing and Ningbo databases.
- api.github.com/repos/AI4HealthUOL/ECG-agingretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2024-04-22, 13 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/31.json→ .entries["ecg-aging"]
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