physhik / ecg-mit-bih

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, https://www.nature.com/articles/s41591-018-0268-3 and also deploy the trained model to a web app using Flask, introduced at

Date Created 2019-03-29 (5 years ago)

Commits 28 (last one 3 years ago)

Stargazers 193 (0 this week)

Watchers 9 (0 this week)

Forks 60

License gpl-3.0

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RepositoryStats indexes 589,134 repositories, of these physhik/ecg-mit-bih is ranked #184,398 (69th percentile) for total stargazers, and #224,707 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #32,799/117,584.

physhik/ecg-mit-bih is also tagged with popular topics, for these it's ranked: flask (#338/1028), cnn (#197/550)

Other Information

physhik/ecg-mit-bih has 4 open pull requests on Github, 0 pull requests have been merged over the lifetime of the repository.

Github issues are enabled, there are 4 open issues and 3 closed issues.

Homepage URL: https://physhik.github.io/2019/03/machine-learns-from-cardiologist-3/

All Topics

cnn ecg cinc flask cardiology mit-bih-arrhythmia

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updated: 2024-11-20 @ 02:23pm, id: 178393941 / R_kgDOCqITVQ