animikhaich / ECG-Atrial-Fibrillation-Classification-Using-CNN

This is a CNN based model which aims to automatically classify the ECG signals of a normal patient vs. a patient with AF and has been trained to achieve up to 93.33% validation accuracy.

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

Commits 8 (last one 3 years ago)

Stargazers 47 (0 this week)

Watchers 3 (0 this week)

Forks 18

License mit

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RepositoryStats indexes 534,880 repositories, of these animikhaich/ECG-Atrial-Fibrillation-Classification-Using-CNN is ranked #445,866 (17th percentile) for total stargazers, and #399,187 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #11,402/14,941.

animikhaich/ECG-Atrial-Fibrillation-Classification-Using-CNN is also tagged with popular topics, for these it's ranked: deep-learning (#6,777/7826), tensorflow (#1,976/2166), classification (#429/507)

Other Information

Homepage URL: http://animikh.me/

All Topics

ecg 1d-cnn patient cnn-keras ecg-signal tensorflow ecg-signals deep-learning 1d-convolution classification cnn-classification atrial-fibrillation

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updated: 2024-06-21 @ 06:10pm, id: 178456854 / R_kgDOCqMJFg