Safeguarding Patient Trust in the Age of AI: Tackling Health Misinformation with Explainable AI
September 04, 2025 Β· Declared Dead Β· π arXiv.org
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Authors
Sueun Hong, Shuojie Fu, Ovidiu Serban, Brianna Bao, James Kinross, Francesa Toni, Guy Martin, Uddhav Vaghela
arXiv ID
2509.04052
Category
cs.IR: Information Retrieval
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
AI-generated health misinformation poses unprecedented threats to patient safety and healthcare system trust globally. This white paper presents an explainable AI framework developed through the EPSRC INDICATE project to combat medical misinformation while enhancing evidence-based healthcare delivery. Our systematic review of 17 studies reveals the urgent need for transparent AI systems in healthcare. The proposed solution demonstrates 95% recall in clinical evidence retrieval and integrates novel trustworthiness classifiers achieving 76% F1 score in detecting biomedical misinformation. Results show that explainable AI can transform traditional 6-month expert review processes into real-time, automated evidence synthesis while maintaining clinical rigor. This approach offers a critical intervention to preserve healthcare integrity in the AI era.
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