Determining domestic violence against women using machine learning methods: The case of Türkiye

The findings of our study demonstrate that ML algorithms have high accuracy rates in determining the frequency and risk factors of domestic violence against women, indicating that they can be used safely.

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Publication Details

Journal
Journal of Evaluation in Clinical Practice
Published
2024-10-13
DOI
https://doi.org/10.1111/jep.14180
Citations
4
Primary Topic
Intimate Partner and Family Violence
Type
article
Field-Weighted Citation Impact
2.11
Controls
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article

Determining domestic violence against women using machine learning methods: The case of Türkiye

Pınar Duru, Fatma Başaran
4 citations
Journal of Evaluation in Clinical Practice
Intimate Partner and Family Violence
2.11
article

Determining domestic violence against women using machine learning methods: The case of Türkiye

Pınar Duru, Fatma Başaran
article en
4 citations

Abstract

The findings of our study demonstrate that ML algorithms have high accuracy rates in determining the frequency and risk factors of domestic violence against women, indicating that they can be used safely.

Journal of Evaluation in Clinical PracticeVol. 31(3)
Ağrı İbrahim Çeçen University (TR), Eskişehir Osmangazi University (TR)
Gender equality
Openalex Percentile: Top 11%
Intimate Partner and Family Violence
2.11
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