I have a dataset of patient records. But I do not know whether he is +ve for a cancer or not. So, I do not have the labels in my dataset.
Now I can run a machine learning models like clustering to generate labels.
For ex: I can run clustering to group the two classes based on similarity and find out who all belong to +ve and -ve class.
Of course, we cannot sit and manual review the patients' data to know whether he is actually +ve for cancer or not.
So when we generate labels via machine learning models like clustering above, is it a recommended approach?
Is it used in industries/real time where people don't have ground truth and only rely on labels based on ML models?
How can we trust these labels generated?
If it's a human I know that it can be trusted. But how do we trust these labels.
Are things like this being used in Industries and how do they tackle the trust issue?