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@@ -37,7 +37,21 @@ It achieves the following results on the evaluation set:
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  ## Model description
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- More information needed
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Intended uses & limitations
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  ## Model description
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+ This model was created by importing the dataset of the photos of ECG image into Google Colab from kaggle here: https://www.kaggle.com/datasets/erhmrai/ecg-image-data/data . I then used the image classification tutorial here: https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb
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+ obtaining the following notebook:
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+ https://colab.research.google.com/drive/1KC6twirtsc7N1kmlwY3IQKVUmSuK7zlh?usp=sharing
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+ The possible classified data are:
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+ <ul>
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+ <li>N: Normal beat</li>
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+ <li>S: Supraventricular premature beat</li>
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+ <li>V: Premature ventricular contraction</li>
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+ <li>F: Fusion of ventricular and normal beat</li>
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+ <li>Q: Unclassifiable beat</li>
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+ <li>M: myocardial infarction</li>
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+ </ul>
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  ## Intended uses & limitations
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