Research
Evaluation of machine learning-based prediction of pregnancy complications and adverse birth outcomes using routine data
Nature ·
The Brief
- A study evaluates machine learning models that predict pregnancy complications and adverse birth outcomes.
- The models are assessed using routine data rather than specialised research datasets.
- Only the title and feed listing were available, so the study's methods and results are not described here.
Why it matters
It tests whether machine learning built on routine health records can flag pregnancy risks, which bears on how such tools might be validated before clinical use.
Who’s affected
- clinicians and researchers in obstetrics and maternal health
- data scientists working on clinical prediction models
- #machine learning
- #pregnancy
- #obstetrics
- #clinical prediction
- #routine data