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智能化心理健康评估:从神经网络到AI Agent的比较研究

何静 戚远博 戴田宇

空军军医大学学报2026,Vol.47Issue(3):370-375,6.
空军军医大学学报2026,Vol.47Issue(3):370-375,6.DOI:10.13276/j.issn.2097-1656.2026.03.009

智能化心理健康评估:从神经网络到AI Agent的比较研究

Intelligent mental health assessment:a comparative study from neural networks to AI Agent

何静 1戚远博 2戴田宇3

作者信息

  • 1. 北京航空航天大学人文与社会科学高等研究院文化传播与管理系,北京 100191||合肥师范学院青少年心理健康与危机智能干预安徽省哲学社会科学重点实验室,安徽 合肥 230001
  • 2. 东华大学人文学院传播系,上海 201620
  • 3. 南昌大学数学与计算机学院计算机科学与技术系,江西南昌 330031
  • 折叠

摘要

Abstract

Mental health issues are a major challenge in global public health.Traditional mental health assessment methods mainly rely on clinical psychologists to conduct interviews,psychological tests,and behavioral observations.Although these methods have certain accuracy in individual assessments,they have long assessment cycles and high costs,making it difficult to meet the needs of large-scale screening.Therefore,there is an urgent need to introduce efficient and intelligent technological means in the field of mental health assessment.The rapid development of artificial intelligence(AI)technology has brought new opportunities for mental health assessment.On the one hand,radial basis function(RBF)neural network simulates the function of brain neurons and uses RBF to process complex mental health data,which has strong adaptability and generalization ability.On the other hand,AI Agent expert system,by integrating expert knowledge and rule-based classification mechanisms,can not only dynamically evaluate and adapt to changes in individual psychological states,but also provide detailed explanations and suggestions,improving the interpretability and credibility of evaluation results.This study introduces RBF neural network and AI Agent expert system into the field of mental health assessment,and compares the advantages and disadvantages of these two representative technologies.The experimental results show that RBF neural network has high accuracy and stability in small and medium-sized data and nonlinear problems,while AI Agent expert system performs well in the interpretability of classification results and knowledge integration,and can achieve efficient mental health assessment at low cost,adapting to different types of assessment tasks.

关键词

心理健康评估/神经网络/AI Agent/AIGC

Key words

mental health assessment/neural networks/AI Agent/AIGC

分类

医药卫生

引用本文复制引用

何静,戚远博,戴田宇..智能化心理健康评估:从神经网络到AI Agent的比较研究[J].空军军医大学学报,2026,47(3):370-375,6.

基金项目

安徽省哲学社会科学重点实验室开放基金重大项目(SYS2023A07) (SYS2023A07)

北京市教育科学"十四五"规划青年专项课题(CGCA23128) (CGCA23128)

空军军医大学学报

OACHSSCD

2097-1656

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