# Machine Learning Based Risk Prediction for Major Adverse Cardiovascular Events

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/machine-learning-based-risk-prediction-for-major-adverse-cardiovascular-events/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Michael Schrempf,Diether Kramer,Stefanie Jauk,Sai Veeranki,Werner Leodolter,Peter P. Rainer |
| Citations | 15 |
| DOI | 10.3233/shti210100 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://ebooks.iospress.nl/pdf/doi/10.3233/SHTI210100 |
| OpenAlex ID | https://openalex.org/W3163888035 |
| PMID | 33965930 |
| Type | book-chapter |
| Year | 2021 |

## Paper authors

- [Stefanie Jauk](https://scholariq.org/researchers/stefanie-jauk/)
- [Diether Kramer](https://scholariq.org/researchers/diether-kramer/)

## Paper journal

- [Studies in health technology and informatics](https://scholariq.org/journals/studies-in-health-technology-and-informatics/)

## 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/)
- [Cardiac Health and Mental Health](https://scholariq.org/topics/cardiac-health-and-mental-health/)
- [Chronic Disease Management Strategies](https://scholariq.org/topics/chronic-disease-management-strategies/)

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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.