Cardiogram engineer here. 97% accuracy refers to a c-statistic (area under the ROC curve) of 0.9740. An example operating point would be 98% sensitivity with 90% specificity.
These important details are often lost in the news. You can some more details on our findings in our blog post:
Just wondering, with such an unbalanced dataset (5,958 negatives, 200 positives), wouldn't have been fairer to use average precision (area under the precision-recall curve) instead of ROC-AUC?
Cardiogram engineer here. 97% accuracy refers to a c-statistic (area under the ROC curve) of 0.9740. An example operating point would be 98% sensitivity with 90% specificity.
These important details are often lost in the news. You can some more details on our findings in our blog post:
https://blog.cardiogr.am/applying-artificial-intelligence-in...