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"The boy who cried wolf" is a story about false positives, so if that's what you want to avoid then you want to get close to 100% specificity, and accept that there are many things that the tool will not catch. If, as you propose, the tool would mainly be used to create a low confidence list of potential problems that will be further reviewed by a human, then casting a wide net and calibrating for high sensitivity instead does make sense.

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The idea is to minimize the false positives "the boy who cried wolf" at the same time mitigate, or better eliminate false negatives. The main reason is that based on the physician in-the-loop, the system can be optimized for sensitivity but can be relaxed for specificity. Of course if can get both 100% sensitivity and specificity it will be great, but in life there's always a trade-off, c'est-la-vie.

In our novel ECG based CVD detection system we can get 100% sensitivity for both arrhythmia and ischemia, with inter-patient validation, not the biased intra-patient as commonly reported in literature even in some reputable conferences/journals. Specificity is still high around 90% but not yet 100% as in sensitivity but due to the physician-in-the-loop approach, which is a diagnostic requirement in the current practice of medicine, this should not be an issue.

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