# Interpretable Deep Models for ICU Outcome Prediction.

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/interpretable-deep-models-for-icu-outcome-prediction/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Zhengping Che,Sanjay Purushotham,Robinder G. Khemani,Yan Liu |
| Citations | 238 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | green |
| OpenAlex ID | https://openalex.org/W2621053657 |
| PMID | 28269832 |
| Type | conference-paper |
| Year | 2016 |

## Paper authors

- [Zhengping Che](https://scholariq.org/researchers/zhengping-che/)

## Paper journal

- [PubMed](https://scholariq.org/journals/pubmed/)

## 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/)
- [Explainable Artificial Intelligence (XAI)](https://scholariq.org/topics/explainable-artificial-intelligence-xai/)
- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)

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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.