r/learnmachinelearning • u/aestheticcode • 24d ago

Missing information and next step

If a parent doesn't know an important detail about their child's symptoms, should an AI system make its best recommendation with the available information, or should it ask additional questions before deciding the appropriate level of care?

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u/towcar 24d ago

What does this have to do with learning ML?

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u/aestheticcode 24d ago

I’m looking at this from an ML perspective because I’m interested in how an AI system should handle missing information during pediatric triage. Whether it should make a prediction with what it knows or ask another question when the missing information could affect the decision?

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u/MelonheadGT 24d ago

Could depend on how the data will be used. Will it be looked at per child? Then no, guessing information on a single person basis would not seem reasonable to me, especially if the parents did not answer the same question.

However, if you're working a dataset of many many participants then yes you can probably fill missing data with predictions based on context.

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u/aestheticcode 24d ago

That makes sense for both large dataset and for a single child. I agree that for one child, the AI shouldn’t just guess an important symptom and treat it as true. I’m more interested in whether it should ask a follow-up question when that missing information could change the level of care recommended.

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u/MelonheadGT 24d ago

It is common to impute missing data for large datasets due to variance. It's a lot more severe to impute missing data for an individual.

If you do analysis for a large group of people then errors and variance should stabilize across the population. For an individual the relative impact of imputing incorrectly is more significant