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Knowledge-augmented Agentic AI for Mental Health Medication Information Seeking

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Knowledge-augmented Agentic AI for Mental Health Medication Information Seeking
TL;DR · WeSearch summary

Integrating them without conflating evidence and anecdote is especially consequential in psychiatry, where poorly contextualised information can amplify fear, nocebo responses, and non-adherence. Here we develop a provenance-aware, knowledge-graph-based multi-agent framework unifying 466,525 Reddit posts, 60,782 WebMD reviews, and twenty years of U.S. FDA Adverse Event Reporting System records for nine antidepressants.

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Original publisherarXiv.org
Canonical URLhttps://arxiv.org/abs/2606.26205
Publication timeFri, 26 Jun 2026 00:00:00 -0400
Retrieval time2026-06-26T05:20:40.893Z
Last seen2026-06-26T05:20:40.893Z
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Excerpt methodFirst ~120 words (~800 chars) of extracted publisher body, fair-use limited.
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Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

Computer Science > Artificial Intelligence arXiv:2606.26205 (cs) [Submitted on 24 Jun 2026] Title:Knowledge-augmented Agentic AI for Mental Health Medication Information Seeking Authors:Huizi Yu, Jian Liu, Wenkong Wang, Lingyao Li, Jiayan Zhou, Zhaoqian Xue, Xiang Li, Xinxin Lin, Zhiying Liang, Zhuoru Wu, Siyuan Ma, Xin Ma, Lizhou Fan View a PDF of the paper titled Knowledge-augmented Agentic AI for Mental Health Medication Information Seeking, by Huizi Yu and 12 other authors View PDF HTML (experimental) Abstract:Patients increasingly seek medication information online, yet safety knowledge for psychiatric drugs is split between regulatory adverse-event records, which are authoritative but abstract, and patient narratives, which are experience-near but unvalidated.

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