Article

Identifying the Presence and Timing of Self-harm in Electronic Mental Health Records Using Privacy-Preserving Local Language Models: Methodological Study

2025-10-29

Abstract excerpt

<h4>Background</h4> Self-harm is the strongest risk factor for suicide and an important outcome for mental health care. Although prevalent in clinical populations, it is often imprecisely captured in routinely collected clinical data, where it is often recorded and stored as unstructured free text. Contemporary language models, such as GPT (OpenAI) and Gemini (Google), can analyse free-text clinical notes, but su...

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Literature Corpus work: 45935378-2030-588b-9ea2-0aec0a63ae94
DOI: 10.1101/2025.10.27.25338892

Open publication

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