Healthcare AI should not optimize only for prediction accuracy or task completion.
It should also handle uncertainty.
A responsible system should recognize incomplete information, distribution shifts, unusual cases, weak evidence, and situations outside its validated operating conditions.
For agentic AI, this becomes critical.
An agent should have defined conditions for continuing, requesting more information, pausing, and escalating to a human.
The architecture should therefore include uncertainty handling as part of the workflow rather than treating it as an afterthought.
Good healthcare AI does not need to know everything.
It needs to know when it does not know enough.
I am open to remote roles globally.
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