# Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/mortality-prediction-in-intensive-care-units-with-the-super-icu-learner/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Romain Pirracchio,Maya Petersen,Marco Carone,Matthieu Resche‐Rigon,Sylvie Chevret,Mark J. van der Laan |
| Citations | 383 |
| DOI | 10.1016/s2213-2600(14)70239-5 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | https://www.ncbi.nlm.nih.gov/pmc/articles/4321691 |
| OpenAlex ID | https://openalex.org/W2150765167 |
| PMID | 25466337 |
| Type | article |
| Year | 2014 |

## Paper authors

- [Romain Pirracchio](https://scholariq.org/researchers/romain-pirracchio/)

## Paper journal

- [The Lancet Respiratory Medicine](https://scholariq.org/journals/the-lancet-respiratory-medicine/)

## Paper primary topic

- [Sepsis Diagnosis and Treatment](https://scholariq.org/topics/sepsis-diagnosis-and-treatment/)

## Paper topics

- [Sepsis Diagnosis and Treatment](https://scholariq.org/topics/sepsis-diagnosis-and-treatment/)
- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)
- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.