# Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/explainable-artificial-intelligence-models-using-real-world-electronic-health/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Seyedeh Neelufar Payrovnaziri,Zhaoyi Chen,Pablo Rengifo‐Moreno,Tim Miller,Jiang Bian,Jonathan H. Chen,Xiuwen Liu,Zhe He |
| Citations | 317 |
| DOI | 10.1093/jamia/ocaa053 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | https://www.ncbi.nlm.nih.gov/pmc/articles/7647281 |
| OpenAlex ID | https://openalex.org/W3024173558 |
| PMID | 32417928 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Jonathan H. Chen](https://scholariq.org/researchers/jonathan-h-chen/)

## Paper journal

- [Journal of the American Medical Informatics Association](https://scholariq.org/journals/journal-of-the-american-medical-informatics-association/)

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

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