# Machine Learning-based Risk of Hospital Readmissions: Predicting Acute Readmissions within 30 Days of Discharge

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/machine-learning-based-risk-of-hospital-readmissions-predicting-acute/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Mirza Mansoor Baig,Ning Hua,Edmond Zhang,R. R. Rejimol Robinson,Delwyn Armstrong,Robyn Whittaker,Tom Robinson,Farhaan Mirza,Ehsan Ullah |
| Citations | 17 |
| DOI | 10.1109/embc.2019.8856646 |
| Fields | Computer Science,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2979804563 |
| PMID | 31946333 |
| Type | conference-paper |
| Year | 2019 |

## Paper authors

- [Ning Hua](https://scholariq.org/researchers/ning-hua/)
- [R. R. Rejimol Robinson](https://scholariq.org/researchers/r-r-rejimol-robinson/)

## Paper primary topic

- [Heart Failure Treatment and Management](https://scholariq.org/topics/heart-failure-treatment-and-management/)

## Paper topics

- [Heart Failure Treatment and Management](https://scholariq.org/topics/heart-failure-treatment-and-management/)
- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)
- [Emergency and Acute Care Studies](https://scholariq.org/topics/emergency-and-acute-care-studies/)

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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.