Title: Mobile-based learning of drug prescription for medical education using artificial intelligence techniques
Authors: Xiaohui Tao; Wee Pheng Goh; Ji Zhang; Jianming Yong; Elizabeth Zhixin Goh; Xueling Oh
Addresses: School of Sciences, University of Southern Queensland, Toowoomba, Queensland, Australia ' School of Sciences, University of Southern Queensland, Toowoomba, Queensland, Australia ' School of Sciences, University of Southern Queensland, Toowoomba, Queensland, Australia ' School of Management and Enterprise, University of Southern Queensland, Toowoomba, Queensland, Australia ' Goh School of Medicine, University of Queensland, Brisbane, Queensland, Australia ' Glory Dental Surgery PTE Ltd., 865 Mountbatten Road, Singapore
Abstract: Medical knowledge is constantly changing with advances in medical sciences and techniques. As such, it is becoming increasingly difficult to keep up to date with current medical information, especially for medical students. Integration of technology into medical education is deemed an efficient way to address the challenge by providing a means of consolidating learning. In particular, the use of Artificial Intelligence (AI) can enable users to have a new experience that helps facilitate their learning and catch-up with the constant advance of knowledge and technology. This in turn can minimise errors and aid better clinical decisions, hence resulting in better patient care. This paper discusses the relevance of mobile learning in medical education and introduces an innovative mobile application design to practice drug prescription in medical education. A prototype system demonstrates the design of the framework and the potential usability of the mobile application for medical students. This is a pioneer exploration of applying AI and mobile technology to help foster the new generation of medical practitioners.
Keywords: mobile-based learning; drug prescription; drug interaction; medical education.
International Journal of Mobile Learning and Organisation, 2021 Vol.15 No.4, pp.392 - 408
Received: 06 Jun 2019
Accepted: 02 Mar 2020
Published online: 26 Oct 2021 *