# Evaluation of machine learning-based prediction of pregnancy complications and adverse birth outcomes using routine data

Source: [Medical research : nature.com subject feeds](https://www.nature.com/articles/s44528-026-00051-0) · 2026-11-11 · Medicine
Page: https://themorning.science/story/evaluation-of-machine-learning-based-prediction-of-pregnancy-complications-and-a-850a400fc0a4be1a
Kind: research · Impact: medium

## In 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.

## Coverage

- [Evaluation of machine learning-based prediction of pregnancy complications and adverse birth outcomes using routine data](https://www.nature.com/articles/s44528-026-00051-0) — Medical research : nature.com subject feeds, 2026-11-11

Tags: machine learning, pregnancy, obstetrics, clinical prediction, routine data

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Brief generated by AI (claude-haiku-5-5) from the reporting listed under Coverage. Headlines belong to their publishers. The Morning Science – https://themorning.science