Academic Journal of Medicine & Health Sciences, 2024, 5(11); doi: 10.25236/AJMHS.2024.051103.
Zhengfeng Yang1,2, Zhen Wen3, Xiaolong Lu1,2, Bo Liu1,2, Runhua Liu1,2
1Department of Health Services Management, Guizhou Medical University, Guiyang, China
2Center of Medicine Economics and Management Research, Guizhou Medical University, Guiyang, China
3International College, Dhurakij Pundit University, Bangkok, Thailand
The application of AI technology in the field of healthcare integration has triggered great changes, this paper explores the new trends in the application of AI technology in the field of healthcare integration, and finds that the application of AI technology in the field of healthcare integration faces the developmental dilemmas of data privacy and security issues, lack of unified technical standards, low acceptance by patients, ethical and moral issues, high technical costs and low sustainability. To this end, this paper proposes that countermeasures should be taken to strengthen data security and privacy protection, establish unified technical standards and norms, enhance patient education and communication, strengthen ethical and moral management, and expand cooperation and investment.
artificial intelligence; healthcare integration; smart healthcare; data privacy; ethics and morality
Zhengfeng Yang, Zhen Wen, Xiaolong Lu, Bo Liu, Runhua Liu. New Trends, Dilemmas and Countermeasures in the Application of Artificial Intelligence Technology in the Field of Combined Medical and Nursing Services. Academic Journal of Medicine & Health Sciences (2024), Vol. 5, Issue 11: 14-18. https://doi.org/10.25236/AJMHS.2024.051103.
[1] Gao, J. J. and C. Lyu, et al. (2022). "Telemedicine virtual reality based skin image in children's dermatology medical system." COMPUTATIONAL INTELLIGENCE 38 (1): 229-248.
[2] Guo, C. X. and H. Li (2022). "Application of 5G network combined with AI robots in personalized nursing in China: A literature review." FRONTIERS IN PUBLIC HEALTH 10.
[3] Jin, Y. C. and D. M. Liu, et al. (2023). "Prediction Model of Elderly Care Willingness Based on Machine Learning." MATHEMATICS 11 (3).
[4] Li, Y. W. and T. N. Zhang, et al. (2020). "Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects." JOURNAL OF INTERNATIONAL MEDICAL RESEARCH 48 (9).
[5] Liu, P. and F. Z. Wang, et al. (2023). "Trends and frontiers of research on telemedicine from 1971 to 2022: A scientometric and visualisation analysis." JOURNAL OF TELEMEDICINE AND TELECARE 29 (9): 731-746.
[6] Reddy, S. and J. Fox, et al. (2019). "Artificial intelligence-enabled healthcare delivery." JOURNAL OF THE ROYAL SOCIETY OF MEDICINE 112 (1): 22-28.
[7] Su, Y. H. (2023). "Visualization design of health detection products based on human-computer interaction experience in intelligent decision support systems." MATHEMATICAL BIOSCIENCES AND ENGINEERING 20 (9): 16725-16743.
[8] Villegas-Ch, W. and J. García-Ortiz (2023). "Toward a Comprehensive Framework for Ensuring Security and Privacy in Artificial Intelligence." ELECTRONICS 12 (18).
[9] Yang, Y. K. and E. Ngai, et al. (2024). "Resistance to artificial intelligence in health care: Literature review, conceptual framework, and research agenda." INFORMATION & MANAGEMENT 61 (4).
[10] Yin, Y. D. and G. H. Xu, et al. (2023). "A 5G-Enabled and Self-Powered Sensor Data Management Scheme for the Smart Medical Platform System." IEEE SENSORS JOURNAL 23 (18): 20904-20915.