neuralnet-mcg
importedsoftware/neuralnet-mcg
CNN to diagnose heart disease in ECG and MCG patients
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- GPL-3.0(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/Smith42/neuralnet-mcg
- Documentation
- unknown
- Tags
- cnn · ecg · machine-learning · mcg · mcg-devices
- 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.
- ecg-mit-bihcnn · ecg
ECG classification using MIT-BIH data, a deep CNN learning implementation of Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network,…
- ECGTransFormcnn · ecg
[Biomedical Signal Processing and Control] ECGTransForm: Empowering adaptive ECG arrhythmia classification framework with bidirectional transformer
LDCNN: A new arrhythmia detection technique with ECG signals using a linear deep convolutional neural network
- lstm-qrs-detectorcnn · ecg
CNN-LSTM based QRS detector for ECG signals
- NABNetcnn · ecg
NABNet: A Nested Attention-guided BiConvLSTM Network for a robust prediction of Blood Pressure components from reconstructed Arterial Blood Pressure waveforms using PPG and ECG Signals
Official source code of "Preprocessing Method for Performance Enhancement in CNN-based STEMI Detection from 12-lead ECG"
- api.github.com/repos/Smith42/neuralnet-mcgretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2018-12-01, 26 stars, license reported as GPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/53.json→ .entries["neuralnet-mcg"]
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