Supervised Natural Language Processing Classification of Violent Death Narratives: Development and Assessment of a Compact Large Language Model

Compact LLMs with sufficient training data can be applied to supervised NLP tasks with a class imbalance in the National Violent Death Reporting System. Simulations of supervised text classification across the model-fitting process of preprocessing and training compact LLM-informed NLP applications to unstructured death narrative data.

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Publication Details

Journal
JMIR AI
Published
2025-06-19
DOI
https://doi.org/10.2196/68212
Citations
3
Primary Topic
Suicide and Self-Harm Studies
Type
article
Field-Weighted Citation Impact
6.92
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article

Supervised Natural Language Processing Classification of Violent Death Narratives: Development and Assessment of a Compact Large Language Model

Susan T. Parker
3 citations
JMIR AI
Suicide and Self-Harm Studies
6.92
article

Supervised Natural Language Processing Classification of Violent Death Narratives: Development and Assessment of a Compact Large Language Model

Susan T. Parker
article en
3 citations

Abstract

Compact LLMs with sufficient training data can be applied to supervised NLP tasks with a class imbalance in the National Violent Death Reporting System. Simulations of supervised text classification across the model-fitting process of preprocessing and training compact LLM-informed NLP applications to unstructured death narrative data.

JMIR AIVol. 4
Northwestern University (US)
Gender equality
Openalex Percentile: Top 3%
Suicide and Self-Harm Studies
6.92
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Supervised Natural Language Processing Classification of Violent Death Narratives: Development and Assessment of a Compact Large Language Model — Susan T. Parker · JMIR AI (2025) | TGRS Research Map | TGRS