# An attention based deep learning model of clinical events in the intensive care unit

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/an-attention-based-deep-learning-model-of-clinical-events-in-the-intensive-care/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Deepak Kaji,John R. Zech,Jun Kim,Samuel K. Cho,Neha Dangayach,Anthony Costa,Eric K. Oermann |
| Citations | 203 |
| DOI | 10.1371/journal.pone.0211057 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0211057&type=printable |
| OpenAlex ID | https://openalex.org/W2913977338 |
| PMID | 30759094 |
| Type | article |
| Year | 2019 |

## Paper authors

- [Jun Kim](https://scholariq.org/researchers/jun-kim/)

## Paper journal

- [PLoS ONE](https://scholariq.org/journals/plos-one/)

## Paper primary topic

- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)

## Paper topics

- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)
- [Sepsis Diagnosis and Treatment](https://scholariq.org/topics/sepsis-diagnosis-and-treatment/)
- [Clinical Reasoning and Diagnostic Skills](https://scholariq.org/topics/clinical-reasoning-and-diagnostic-skills/)

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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.