A self-supervised framework for laboratory data imputation in electronic health records
Abstract Background Laboratory data in electronic health records (EHRs) is an effective source of information to characterize patient populations, inform accurate diagnostics and treatment decisions, and fuel research studies. However, despite their value, laboratory values are underutilized due to...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-025-00973-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|