We’re going to tell you something.
We’ll tell you and then you can do whatever you want with the information.
You’ll do it anyway, so whatever.
We believe that one of the most amazing things about AI is that it will save a lot of expensive tests.
This is important because when people think of AI, they think of improving diagnosis.
They think of an AI that can detect a polyp or stratify risks. Or they think about risk stratification.
An AI that tells us that these patients here are more likely to decompensate and then we call them.
All of that is great.
But imagine an AI that tells you which patients are more likely to test positive for a genetic test.
A test that is necessary to prescribe medication, for example.
A test that is expensive and not everyone can afford.
Well, we talked to a pharmaceutical company that had this problem.
We spoke to their headquarters in the US, and they said, “Hey, you Machine Learning geniuses. Let’s see if you can really do it.”
We said, “But keep in mind that no algorithm in the world can correctly predict all positive or negative results. It’s about finding more positives for the same amount of money, which is what you and the oncologists want.”
They said ok. That’s fine.
And we don’t know, maybe you want to know if it worked.
If the AI pre-genetic test is worth it. If it’s something that can be applied to all tests in this situation.
But ultimately, what does it matter if we tell you?
If you’re not going to do anything.
If you’re going to keep thinking that AI is “the future.”
If you only like innovation when it involves putting on virtual reality glasses and going on a fake roller coaster.
But not when there are possibilities to change your job with real and cutting-edge technology.
You would love to, but your boss, Legal, or your parents won’t let you.
Anyway, we wish you a great day.
PS. AI pre-molecular tests in 2023, here.
PS 2. In 2024? In the future? No, in 2023. Here.