This is a common misconception I see in my patients all the time. Tests aren’t perfect and human bodies aren’t perfect. Even if a test has 99% specificity for a condition, if less than 1% of people getting the test has the condition at the time of the test, there will be more false positives than true positives. False positives require further investigations which have higher risks (incl death) just like true positives. Likewise, tests may show something that is indeed there, a mass for example, but that would never cause a clinically significant impact (the patient would otherwise never know they had it and it wouldn’t hurt their health). But that may still then lead to further investigations, which may be more invasive (read risk of death and morbidity) or at least anxiety in patients about what is going on with them.

This is a long way of saying, it would be bad to test everyone with an MRI machine, let alone repeatedly. (It would be great if MRI costs were cheaper however).

Well assuming you were to take an MRI test once a month I think you could start to read the data after 1 year and be able to infer with AI the velocity/acceleration of any change in the person?

There are practical issues there. Liquid helium is relatively expensive and scarce, magnetic fields from the machine by definition need to be high to get good results, and to throw more fun into the mix you need to stop external radio interference from getting at the machine. Could you get the cost down to "specialised doctor's office" levels? Maaaaybe. Does AI have a role to play in that? Not one bit.

Are there alternative fluids to liquid helium that could be used for cooling the magnets?

Liquid nitrogen is one alternative. Some further work is being done on room temperature superconductors, which obviates the need for any kind of cooling.