# Development and external validation of a machine learning model for 28-day mortality in patients with gastrointestinal bleeding and chronic kidney disease

Source: [Medical research : nature.com subject feeds](https://www.nature.com/articles/s41598-026-77207-z) · 2026-11-10 · Medicine
Page: https://themorning.science/story/development-and-external-validation-of-a-machine-learning-model-for-28-day-morta-6fc578d805f225e7
Kind: research · Impact: medium

## In brief

- A study reports the development and external validation of a machine learning model for 28-day mortality in patients with gastrointestinal bleeding and chronic kidney disease.
- The article was listed in a nature.com subject feed on 2026-11-10; no summary or model performance figures were provided.

## Why it matters

A validated tool for predicting 28-day mortality could help clinicians identify high-risk patients with gastrointestinal bleeding and chronic kidney disease, though the available source does not report accuracy results.

## Coverage

- [Development and external validation of a machine learning model for 28-day mortality in patients with gastrointestinal bleeding and chronic kidney disease](https://www.nature.com/articles/s41598-026-77207-z) — Medical research : nature.com subject feeds, 2026-11-10

Tags: machine learning, gastrointestinal bleeding, chronic kidney disease, mortality prediction, clinical research

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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