Medical-Event-Data-Standard / Medical-Event-Data-Standard/meds
How do we encode multi-label or sparse task labels?
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- Dominant language
- Python
- Stars
- 134
- Forks
- 12
- PR merge metrics
- No merged PRs in 30d
Description
In our label schema, if a task is multi-label (e.g., predict all the diagnoses a patient will receive in this stay), how do we want to encode that? What if a task is sparse and multi-label (e.g., predict the max lab value that will be seen for all labs measured in this stay)?
I don't think this is urgent at all, but it is worth contemplating to either capture in documentation or in future versions (or to have a place for catching discussions about it)
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No file, test, or entry point is named. Start by reviewing the existing label schema and related documentation, then determine how multi-label and sparse multi-label tasks should be represented; done means the encoding decision is agreed and captured in documentation or a future-version plan.
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Assessment
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100