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The metric to actually pay attention to is the area under that curve (AUC or AUROC). This can sorta be interpreted the same as the accuracy where 1 is perfect, 0 is exactly opposite of the right answers (so you could just reverse the answers and have the right ones - kinda like scoring 0% on a true/false quiz) and 0.5 is no better than random guessing. Honestly impressive the success rate. It'll need more replicate studies but 1000 samples with 94% are pretty damn good for an instant-read. Accuracy means nothing when you have imbalanced data. I can also predict if a random person off the street has COVID with 90-something% accuracy. I’ll just say nobody has it and since the number of people who actually have COVID is less than 10% in almost every population, I’ll have greater than 90% accuracy.

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