Scholarlink

Current e-government services for public health fail to fully address citizens’ needs due to several limitations. Aiming to augment the effectiveness of these services, this paper introduces a public health QA assistant that seamlessly integrates Knowledge Graphs, LLMs and Explainable AI techniques. The proposed approach builds on the power of LLMs and incorporates symbolic reasoning to improve citizen awareness of medical issues and enhance trust in health services. By automating public health QA and providing transparent, user-friendly explanations, the proposed assistant may foster citizen participation and understanding without requiring technical expertise, thus significantly increasing the social impact of public health services. This work also intends to reveal a series of insights about the way that modern AI-enhanced public health systems should be developed.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Integrating Knowledge Graphs, Large Language Models and Explainable AI Techniques to Improve Public Health Question Answering

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Nikolaos Giarelis,
  • Charalampos Mastrokostas,
  • Ilias Siachos,
  • Nikos Karacapilidis

摘要

Current e-government services for public health fail to fully address citizens’ needs due to several limitations. Aiming to augment the effectiveness of these services, this paper introduces a public health QA assistant that seamlessly integrates Knowledge Graphs, LLMs and Explainable AI techniques. The proposed approach builds on the power of LLMs and incorporates symbolic reasoning to improve citizen awareness of medical issues and enhance trust in health services. By automating public health QA and providing transparent, user-friendly explanations, the proposed assistant may foster citizen participation and understanding without requiring technical expertise, thus significantly increasing the social impact of public health services. This work also intends to reveal a series of insights about the way that modern AI-enhanced public health systems should be developed.