# Using modern risk engines and machine learning/artificial intelligence to predict diabetes complications: A focus on the BRAVO model

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/using-modern-risk-engines-and-machine-learning-artificial-intelligence-to/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Hui Shao,Lizheng Shi,Yilu Lin,Vivian Fonseca |
| Citations | 23 |
| DOI | 10.1016/j.jdiacomp.2022.108316 |
| Fields | Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4300687305 |
| PMID | 36201893 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Yilu Lin](https://scholariq.org/researchers/yilu-lin/)

## Paper journal

- [Journal of Diabetes and its Complications](https://scholariq.org/journals/journal-of-diabetes-and-its-complications/)

## Paper primary topic

- [Diabetes Treatment and Management](https://scholariq.org/topics/diabetes-treatment-and-management/)

## Paper topics

- [Diabetes Treatment and Management](https://scholariq.org/topics/diabetes-treatment-and-management/)
- [Diabetes Management and Research](https://scholariq.org/topics/diabetes-management-and-research/)
- [Diabetes, Cardiovascular Risks, and Lipoproteins](https://scholariq.org/topics/diabetes-cardiovascular-risks-and-lipoproteins/)

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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.