Exploring Complex Mental Health Symptoms via Classifying Social Media Data with Explainable LLMs

2024/12/09 by Kexin Chen, Noelle Lim, Chen, Kexin +5
Computer Science · Psychology · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning in Healthcare #Mental Health via Writing

paper · pdf · doi:10.48550/arxiv.2412.10414

openalex publication_date 2024/12/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We propose a pipeline for gaining insights into complex diseases by training LLMs on challenging social media text data classification tasks, obtaining explanations for the classification outputs, and performing qualitative and quantitative analysis on the explanations. We report initial results on predicting, explaining, and systematizing the explanations of predicted reports on mental health concerns in people reporting Lyme disease concerns. We report initial results on predicting future ADHD concerns for people reporting anxiety disorder concerns, and demonstrate preliminary results on visualizing the explanations for predicting that a person with anxiety concerns will in the future have ADHD concerns.

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