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Related Experiment Video

Updated: May 2, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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Examining user-AI interaction patterns in health-Information queries.

Jade T Wang1, Hyun Woo Chung1, Giang N Do1

  • 1Department of Information Systems, College of Business, University of Nevada, Reno, 1664 N. Virginia Street, NV 89557, USA.

International Journal of Medical Informatics
|April 30, 2026
PubMed
Summary

Individuals use generative artificial intelligence (GAI) for health information, including symptom exploration and medical education. These AI tools act as preliminary support, potentially guiding users toward professional medical consultation.

Keywords:
Generative artificial intelligenceOnline health information seekingSupport vector machineText-mining

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Area of Science:

  • Health Informatics
  • Artificial Intelligence in Healthcare
  • Human-Computer Interaction

Background:

  • Growing use of generative artificial intelligence (GAI) tools for information retrieval.
  • Limited understanding of how individuals engage with GAI for health-related queries.
  • Need to analyze real-world user interactions with GAI in the health domain.

Purpose of the Study:

  • To investigate patterns of user interaction with GAI for health information seeking.
  • To categorize the types of health-related questions users pose to GAI.
  • To understand the role of GAI as a health information resource and support tool.

Main Methods:

  • Analysis of a dataset comprising user-GAI chat logs.
  • Application of data and text-analytic methods for interaction categorization.
  • Utilization of supervised machine learning, specifically Support Vector Machines (SVMs), for theme identification.

Main Results:

  • Users frequently employ GAI for symptom exploration and medical education.
  • GAI is utilized for mental health support and general health advice.
  • Identified recurrent themes in user queries and interactions with GAI.

Conclusions:

  • GAI tools serve as significant informational resources for health queries.
  • GAI can function as a preliminary support tool, influencing user health knowledge.
  • GAI interactions may encourage users to seek professional medical consultations.