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Comparative analysis of BERT-based and generative large language models for detecting suicidal ideation: a

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Microsoft Bing/GPT-4 demonstrated superior performance in detecting suicidal ideation in Brazilian Portuguese texts compared to other large language models and BERT variations. This artificial intelligence advancement shows promise for mental health support but requires clinical validation.

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Area of Science:

  • Natural Language Processing
  • Artificial Intelligence in Mental Health
  • Computational Linguistics

Background:

  • Artificial intelligence (AI) shows potential for detecting suicidal ideation in text.
  • BERT-based models excel in text classification tasks.
  • Large Language Models (LLMs) can address queries without specific training.

Purpose of the Study:

  • To compare the performance of three BERT model variations and three LLMs (Google Bard, Microsoft Bing/GPT-4, OpenAI ChatGPT-3.5) in identifying suicidal ideation in Brazilian Portuguese texts.
  • To evaluate the effectiveness of AI models in a nonclinical text setting.

Main Methods:

  • A dataset of 2,691 non-suicidal and 1,097 suicidal ideation sentences was used, with 100 selected for testing.
  • BERT models underwent preprocessing, hyperparameter optimization, and cross-validation.
  • LLMs were evaluated using zero-shot prompting engineering.

Main Results:

  • Microsoft Bing/GPT-4 achieved the highest performance with 98% accuracy.
  • Fine-tuned BERT models showed strong results: BERTimbau-Large (96%), BERTimbau-Base (94%), and BERT-Multilingual (87%).
  • Google Bard (62%) and OpenAI ChatGPT-3.5 (81%) had lower accuracy compared to Bing/GPT-4 and fine-tuned BERT models.

Conclusions:

  • The high recall capacity of these AI models suggests a potential for reducing misclassification of at-risk individuals.
  • While promising for supporting suicidal ideation detection, these models lack clinical validation for patient monitoring.
  • Caution is advised when using these AI tools to assist healthcare professionals in detecting suicidal ideation.