It's a bit difficult to say, isn't it? The headline is using the term accuracy correctly, the reader might be ascribing the meaning you are to it, especially if they are non technical. As was the parent comment.

My goal in pointing out the difference was not to be snarky. It was to point out the very real statistical consequences. Any model can be accurate on a sufficiently biased dataset, but what matters once a screening test hits the real world are the precision (positive predictive value) and negative predictive value. These are the hurdles that the test will have to pass to see widespread adoption.