Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

November 29, 2024


Pages


DOI

Article

Ethical Risks and Legal Compliance of Big Data Analytics Technology in Medical Privacy Protection

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Authors

Yulian Ma Affiliation:
School of Marxism, Bengbu Medical University, Bengbu, Anhui, 233000, China
and Chang Liu Affiliation:
Department of Journal Editorial, Bengbu Medical University, Bengbu, Anhui, 233000, China


Abstract

While big data analytics technology plays an important role in medical privacy protection, ethical risks and legal compliance issues are becoming more prominent. The study applies logistic regression models to analyse the ethical risk factors affecting medical privacy leakage. A hierarchical linear model is then applied to explore the impact of different legal factors on medical data compliance. Logistic regression analysis shows that corporate credibility, the ethical status of research units, institutional factors, and financial factors have a greater impact on the status of ethical risky behaviors. Hierarchical regression analyses show that different legal factors have different impacts on medical data compliance. Accordingly, this paper proposes countermeasures to avoid ethical risks. The paper suggests that ethical risk avoidance should start from four aspects: laws and regulations, industry self-regulation, technological innovation, and citizen quality. To enhance legal compliance, we should adhere to the four principles of principle, standardization, policy, and local legislation first.


Keywords

Logistic regression model, Hierarchical linear model, Big data analysis technology, Medical privacy protection., 97P10


Citation

Ma, Y. & Liu, C. (2024). Ethical risks and legal compliance of big data analytics technology in medical privacy protection. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-3649

Published by: Engineering Journals

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