EXPLORING PERCEPTION OF INDIVIDUALS ON USING ARTIFICIAL INTELLIGENCE FOR REPORTING SIDE EFFECTS OF MEDICINES    

Authors : 1. Ritu Raj, Student, IIHMR University; 2. Dr. Vinod Kumar SV, Professor, IIHMR University

Publishing Date : 2025

DOI : https://doi.org/10.52458/9789349381452.nsp.2025.eb.ch-17

ISBN : 978-93-49381-78-0

Pages : 80-85

Chapter id : IIHMR/NSP/EB/TSLHSTIOE/2025/Ch-17

Abstract :

Keywords :

Cite : Raj, R., & SV, V. K. (2025). Exploring Perception Of Individuals On Using Artificial Intelligence For Reporting Side Effects Of Medicines (1st ed., pp. 80-85). Noble Science Press. https://doi.org/10.52458/9789349381452.nsp.2025.eb.ch-17

References :

1. Shermock, S. B., Shermock, K. M., & Schepel, L. L. (2023). Closed-loop medication management with an electronic health record system in US And Finnish hospitals. International Journal of Environmental Research and Public Health, 20(17), 6680.
2. Zhou, S., Kang, H., Yao, B., & Gong, Y. (2018). Analyzing medication error reports in clinical settings: an automated pipeline approach. In AMIA Annual Symposium Proceedings (Vol. 2018, p. 1611). American Medical Informatics Association.
3. Valinciute, A., Gerbutaviciene, R. J., Paukstaitiene, R., & Kubiliene, L. (2023, April). Pharmacovigilance and adverse drug reaction reporting among the general public in Lithuania: A cross-sectional study. In Healthcare (Vol. 11, No. 8, p. 1133). MDPI.
4. Banovac, M., Candore, G., Slattery, J., Houÿez, F., Haerry, D., Genov, G., & Arlett, P. (2017). Patient reporting in the EU: analysis of EudraVigilance data. Drug Safety, 40, 629-645.
5. Huang, Y. L., Moon, J., & Segal, J. B. (2014). A comparison of active adverse event surveillance systems worldwide. Drug safety, 37, 581-596.