Zhang, X., Elmansy, R. orcid.org/0000-0001-5148-0049 and Liu, J. (2024) Artificial Intelligence in Medication Management for Alzheimer's Patients in China. In: Kalra, J., (ed.) Healthcare and Medical Devices. 15th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences, 24-27 Jul 2024, Nice, France. AHFE International , pp. 28-39. ISBN 978-1-964867-06-9
Abstract
Abstract: This study provides a comprehensive overview of artificial intelligence (AI) in China's pharmaceutical Alzheimer's management by examining past research. The focus is on critical factors that affect medicine adherence and major AI breakthroughs and trends. A systematic analysis examines how artificial intelligence can monitor medication adherence, give reminders, and discover drug interactions. These apps may improve patient adherence, therapeutic efficacy, and quality of life. However, literature gaps emphasise the need for more research. In conclusion, future projects should address these gaps to serve patients better, improve treatment outcomes, and navigate ethical and policy issues, advancing Alzheimer's drug management.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2024. Published by AHFE Open Access. The authors of papers published in the AHFE Open Access Proceedings will retain full copyrights as specified by the provisions of the Creative Commons: http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Alzheimer's, Artificial Intelligence, Medication Management, Medication Adherence |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Arts, Humanities and Cultures (Leeds) > School of Design (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 Nov 2024 12:13 |
Last Modified: | 13 Nov 2024 12:13 |
Status: | Published |
Publisher: | AHFE International |
Identification Number: | 10.54941/ahfe1004834 |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:219556 |