GPTFX: A Novel GPT-3 Based Framework for Mental Health Detection and Explanations.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 37903039.
- Also identified by DOI 10.1109/JBHI.2023.3328350.
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Abstract
This paper introduces a novel approach GPTFX, an AI-based mental detection with GPT frameworks. This approach leverages GPT embeddings and the fine-tuning of GPT-3. This approach exhibits superior performance in both classifying mental health disorders and generating explanations with accuracy of around 87% in classification and Rouge-L of around 0.75. We utilized GPT embeddings with machine learning models for the classification of mental health disorders. Additionally, GPT-3 was fine-tuned for generating explanations related to the predictions made by these machine learning models. Notably, the proposed algorithm proves well-suited for real-time monitoring of mental health by deploying in AI-IoMT devices, as it has demonstrated greater reliability when compared to traditional algorithms.