Quantum Artificial Intelligence in Healthcare: Urgent Opportunities and Gaps in Epilepsy-Psychiatry

AbstractQuantum artificial intelligence (QAI) combines quantum computing and AI to analyze complex healthcare data beyond classical limits. These methods offer new capabilities for discovering nonlinear neurobehavioral patterns, which could support precision psychiatry and the integration of epilepsy and mental health care. This systematic review analyzed published studies applying QAI to healthcare. Most work focused on imaging and drug discovery. Hybrid models combining quantum and classical algorithms showed early promise in small, noisy, or complex datasets. However, no studies addressed epilepsy-related psychiatric comorbidities, despite urgent needs in this domain. This poster identifies translational gaps and proposes future directions including the use of QAI for neuropsychiatric data, model interpretability, and privacy-preserving learning. Presented at: AMIA Annual Symposium 2025Location: Atlanta, Georgia, USADates: November 15 to 19, 2025 Authors: Joanne Osuchukwu, MD; Judith W. Dexheimer, PhD; John P. Pestian, PhD, MBA Affiliations:Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical CenterDepartment of Biomedical Informatics, University of Cincinnati College of MedicineDepartment of Pediatrics, University of Cincinnati College of Medicine and Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA Original abstract published in the AMIA proceedings:https://knowledge.amia.org/A2025/content?act=2025Annuala949