# Machine learning applied to electronic health record data in home healthcare: A scoping review

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/machine-learning-applied-to-electronic-health-record-data-in-home-healthcare-a/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Mollie Hobensack,Jiyoun Song,Danielle Scharp,Kathryn H. Bowles,Maxim Topaz |
| Citations | 45 |
| DOI | 10.1016/j.ijmedinf.2022.104978 |
| Fields | Computer Science,Health Professions,Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | https://www.ncbi.nlm.nih.gov/pmc/articles/9869861 |
| OpenAlex ID | https://openalex.org/W4313443394 |
| PMID | 36592572 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Jiyoun Song](https://scholariq.org/researchers/jiyoun-song/)

## Paper journal

- [International Journal of Medical Informatics](https://scholariq.org/journals/international-journal-of-medical-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/)
- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)
- [Electronic Health Records Systems](https://scholariq.org/topics/electronic-health-records-systems/)

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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.