I can't help but think some of the barriers here involved proving the software in a situation decidedly different than a clinical setting. I would not be surprised if an immigration medical officer developed different views about diseases than a GP or ER doctor. They're not treating the person, they're not in a doctor-patient relationship with the person, they're not really even "diagnosing" the person, they're just deciding whether they're "too sick" to come into the country. Maybe if the person looks messed up in some other way, their chest x-ray gets interpreted a little more strictly.
>> I can't help but think some of the barriers here involved proving the software in a situation decidedly different than a clinical setting.
Totally agree. But science moves in baby steps and progress builds on progress. We started ML by doing linear regression. Then we moved onto recognizing digits. Then we moved onto recognizing cats. Suddenly, Google Photos can find a friend of mine from 1994 in images it appears to have automatically sucked up. That is amazing progress.
Similarly, our viewpoint as co-founders in the space was to solve a single use-case amazingly well and prove AUC and cost/value metrics. The field wont be moved by me or you, it will be moved by dozens of teams building upon each other.
But AI theater being good enough to replace no-stakes (because no one is liable to anyone for any errors, in either direction) medical theater is a step, just not as big a step or relevant to any use case of any importance as being sold upthread
