mlsanityData to 14 Oct 2026

Evaluating Large Language Models for Anxiety and Depression Classification using Counseling and Psychotherapy Transcripts

arXiv 2407.13228 ↗First posted 18 Jul 2024cs.CL cs.CY cs.ETcited by 0

Not on the map. Why?

Abstract (arXiv)

We aim to evaluate the efficacy of traditional machine learning and large language models (LLMs) in classifying anxiety and depression from long conversational transcripts. We fine-tune both established transformer models (BERT, RoBERTa, Longformer) and more recent large models (Mistral-7B), trained a Support Vector Machine with feature engineering, and assessed GPT models through prompting. We observe that state-of-the-art models fail to enhance classification outcomes compared to traditional machine learning methods.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 41 references that are in the map. First posted on arXiv 18 Jul 2024.

Builds on

14 of 41 references.

References · 14

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2020Longformer: The Long-Document Transformercited by 3,413
  4. 2023Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarizationcited by 246
  5. 2022GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Recordscited by 238
  6. 2013Crowdsourcing a Word-Emotion Association Lexiconcited by 196
  7. 2021MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcarecited by 161
  8. 2023Large Language Models to Identify Social Determinants of Health in Electronic Health Recordscited by 55
  9. 2023A Comparative Study of Pretrained Language Models for Long Clinical Textcited by 35
  10. 2022Efficient Classification of Long Documents Using Transformerscited by 30
  11. 2023A Review of and Roadmap for Data Science and Machine Learning for the Neuropsychiatric Phenotype of Autismcited by 11
  12. 2023Robust language-based mental health assessments in time and space through social mediacited by 5
2 more
  1. 2021EmoDNN: Understanding emotions from short texts through a deep neural network ensemblecited by 2
  2. 2023A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Healthcited by 2

Built on by

Not cited yet.