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 19
License mit
Ranking

RepositoryStats indexes 616,861 repositories, of these animikhaich/ECG-Atrial-Fibrillation-Classification-Using-CNN is ranked #498,562 (19th percentile) for total stargazers, and #433,549 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #13,403/18,375.

animikhaich/ECG-Atrial-Fibrillation-Classification-Using-CNN is also tagged with popular topics, for these it's ranked: deep-learning (#7,403/8702),  tensorflow (#2,066/2285),  classification (#474/557)

Other Information

Homepage URL: http://animikh.me/

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updated: 2024-10-06 @ 09:36pm, id: 178456854 / R_kgDOCqMJFg