# Generating synthetic mixed-type longitudinal electronic health records for artificial intelligent applications

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/generating-synthetic-mixed-type-longitudinal-electronic-health-records-for/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jin Li,Jin Li,Benjamin J. Cairns,Jingsong Li,Jingsong Li,Tingting Zhu |
| Citations | 108 |
| DOI | 10.1038/s41746-023-00834-7 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.nature.com/articles/s41746-023-00834-7.pdf |
| OpenAlex ID | https://openalex.org/W4378576258 |
| PMID | 37244963 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Jingsong Li](https://scholariq.org/researchers/jingsong-li/)

## Paper journal

- [npj Digital Medicine](https://scholariq.org/journals/npj-digital-medicine/)

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

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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.