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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20251016T135126Z
LOCATION:Grand C/D North
DTSTART;TZID=America/Chicago:20251015T121000
DTEND;TZID=America/Chicago:20251015T123000
UID:HFESAM_ASPIRE 2025_sess190_LECT390@linklings.com
SUMMARY:Multi-Agent Systems (MAS) for Remote Healthcare with Enhanced Effi
 ciency and Trust through Quantum-Model Methodology and Validation
DESCRIPTION:Zehaan Walji, Reyansh BADHWAR, and Parshva Dave (University of
  Calgary); Changwon Son (Texas Tech University); Junho Park (University of
  Calgary); and Shane Virani (University of Calgary, w21c)\n\nArtificial in
 telligence (AI) chatbots have improved rapidly. However, these systems sti
 ll face challenges in complex and time-sensitive issues where real-time aw
 areness is imperative, such as remote emergent care. To address these limi
 tations, a Multi-Agent System (MAS) was developed that employs a collectio
 n of AI agents with unique and distinct tasks, ranging from symptom analys
 is and user proficiency to risk assessment and information verification. I
 n conjunction, these agents work together to enhance the clarity of output
  and thereby mitigate the hallucinatory effects associated with traditiona
 l single-agent systems. The trust dynamics of the human-AI team were measu
 red quantitatively using a novel quantum model, implemented with Quiskit. 
 In human subject experiments, the MAS system significantly reduced the num
 ber of follow-up questions and achieved higher trust scores than the singl
 e-agent system, indicating the model's validity. These results suggest tha
 t MAS-based systems can substantially improve the reliability and effectiv
 eness of remote emergency care, offering a promising new direction for dig
 ital healthcare support. Future research will extend validation across bro
 ader populations and emergency scenarios.\n\nTrack: Health Care\n\nSession
  Chair: Yuval Bitan (Ben-Gurion University of the Negev)\n\n
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