# Machine learning for real-time prediction of complications in critical care: a retrospective study

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/machine-learning-for-real-time-prediction-of-complications-in-critical-care-a/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Alexander Meyer,Dina Zverinski,Boris Pfahringer,Jörg Kempfert,Titus Kühne,Simon Sündermann,Christof Stamm,Thomas Hofmann,Volkmar Falk,Carsten Eickhoff |
| Citations | 364 |
| DOI | 10.1016/s2213-2600(18)30300-x |
| Fields | Computer Science,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2892592994 |
| PMID | 30274956 |
| Type | article |
| Year | 2018 |

## Paper authors

- [Jörg Kempfert](https://scholariq.org/researchers/jorg-kempfert/)

## 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/)
- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)
- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)

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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.