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-[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
-[![Website shields.io](https://img.shields.io/website-up-down-green-red/http/shields.io.svg)](http://bestecgclassifier.herokuapp.com)
-
-
-# Links to model notebooks
-[2D CNN](https://github.com/hardikroutray/ECG/blob/main/scripts/CNN2D_ECG.ipynb)   
-[1D CNN](https://github.com/hardikroutray/ECG/blob/main/scripts/Multi_lead_1dCNN.ipynb) 
-<!-- [Random Forest] (https://github.com/hardikroutray/ECG/blob/main/Multi-Lead-DataFrame-Update-Copy1_0528.ipynb)
-[Misc] (https://github.com/hardikroutray/ECG/blob/main/Iftah_Classification%20Analysis_full_features.ipynb)
- -->
-
-
-
-# ECG
-
-We classify various cardiovascular conditions from Electrocardiogram (ECG) images [1]. We also study the ECG of COVID-19 patients to identify potential cardiac injury due to SARS CoV 2. We perform both image and time series classification. Our 1D CNN model using time series achieves 95 % accuracy in classifying cardiac disorders including COVID-19.
-
-
-# Application
-https://bestecgclassifier.herokuapp.com/
-
-
-# Preprocessing
-
-![alt text]( https://github.com/hardikroutray/ECG/blob/main/app/images/data_prep1.png )
-
-# Best Performance (95 % Accuracy)
-
-Time series classification using 1D CNN <br>
-![alt text](https://github.com/hardikroutray/ECG/blob/main/app/images/1d_CNN_vis.png)
-
-
-
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+[![Website shields.io](https://img.shields.io/website-up-down-green-red/http/shields.io.svg)](http://bestecgclassifier.herokuapp.com)
+
+
+# Links to model notebooks
+[2D CNN](https://github.com/hardikroutray/ECG/blob/main/scripts/CNN2D_ECG.ipynb) &nbsp; 
+[1D CNN](https://github.com/hardikroutray/ECG/blob/main/scripts/Multi_lead_1dCNN.ipynb) 
+<!-- [Random Forest] (https://github.com/hardikroutray/ECG/blob/main/Multi-Lead-DataFrame-Update-Copy1_0528.ipynb)
+[Misc] (https://github.com/hardikroutray/ECG/blob/main/Iftah_Classification%20Analysis_full_features.ipynb)
+ -->
+
+
+
+# ECG
+
+We classify various cardiovascular conditions from Electrocardiogram (ECG) images [1]. We also study the ECG of COVID-19 patients to identify potential cardiac injury due to SARS CoV 2. We perform both image and time series classification. Our 1D CNN model using time series achieves 95 % accuracy in classifying cardiac disorders including COVID-19.
+
+
+# Application
+https://bestecgclassifier.herokuapp.com/
+
+
+# Preprocessing
+
+![alt text]( https://github.com/hardikroutray/ECG/blob/main/app/images/data_prep1.png?raw=true)
+
+# Best Performance (95 % Accuracy)
+
+Time series classification using 1D CNN <br>
+![alt text](https://github.com/hardikroutray/ECG/blob/main/app/images/1d_CNN_vis.png?raw=true)
+
+
+