# Mining fall-related information in clinical notes: Comparison of rule-based and novel word embedding-based machine learning approaches

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/mining-fall-related-information-in-clinical-notes-comparison-of-rule-based-and/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Maxim Topaz,Ludmila Murga,Katherine M. Gaddis,Margaret V. McDonald,Ofrit Bar‐Bachar,Yoav Goldberg,Kathryn H. Bowles |
| Citations | 110 |
| DOI | 10.1016/j.jbi.2019.103103 |
| Fields | Computer Science,Nursing |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://www.sciencedirect.com/science/article/pii/S1532046419300218/pdf |
| OpenAlex ID | https://openalex.org/W2909322947 |
| PMID | 30639392 |
| Type | article |
| Year | 2019 |

## Paper authors

- [Maxim Topaz](https://scholariq.org/researchers/maxim-topaz/)
- [Kathryn H. Bowles](https://scholariq.org/researchers/kathryn-h-bowles/)

## Paper journal

- [Journal of Biomedical Informatics](https://scholariq.org/journals/journal-of-biomedical-informatics/)

## Paper primary topic

- [Nursing Diagnosis and Documentation](https://scholariq.org/topics/nursing-diagnosis-and-documentation/)

## Paper topics

- [Nursing Diagnosis and Documentation](https://scholariq.org/topics/nursing-diagnosis-and-documentation/)
- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)
- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)

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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.