Cheap Ways of Extracting Clinical Markers from Texts
A Sandu, T Mihailescu, S Nisioi - arXiv preprint arXiv:2403.11227, 2024 - arxiv.org
This paper describes the work of the UniBuc Archaeology team for CLPsych's 2024 Shared
Task, which involved finding evidence within the text supporting the assigned suicide risk …
Task, which involved finding evidence within the text supporting the assigned suicide risk …
Enhancing suicidal behavior detection in EHRs: A multi-label NLP framework with transformer models and semantic retrieval-based annotation
Background: Suicide is a leading cause of death worldwide, making early identification of
suicidal behaviors crucial for clinicians. Current Natural Language Processing (NLP) …
suicidal behaviors crucial for clinicians. Current Natural Language Processing (NLP) …
[PDF][PDF] Extraction and summarization of suicidal ideation evidence in social media content using large language models
This paper explores the use of Large Language Models (LLMs) in analyzing social media
content for mental health monitoring, specifically focusing on detecting and summarizing …
content for mental health monitoring, specifically focusing on detecting and summarizing …
Su-RoBERTa: A Semi-supervised Approach to Predicting Suicide Risk through Social Media using Base Language Models
In recent times, more and more people are posting about their mental states across various
social media platforms. Leveraging this data, AI-based systems can be developed that help …
social media platforms. Leveraging this data, AI-based systems can be developed that help …
Extracting and Summarizing Evidence of Suicidal Ideation in Social Media Contents Using Large Language Models
This paper explores the use of Large Language Models (LLMs) in analyzing social media
content for mental health monitoring, specifically focusing on detecting and summarizing …
content for mental health monitoring, specifically focusing on detecting and summarizing …