Author(s)

Lianti Jiang ¹

Affiliation(s)

¹ Grandall Law Firm (Tianjin), Tianjin, 300042, China

Corresponding Author

Lianti Jiang

ABSTRACT

Although the large-scale clinical application of medical artificial intelligence has driven revolutionary changes in medical services, it has also triggered a complex web of legal risks. This article conducts a comprehensive analysis of typical risks inherent in medical artificial intelligence, such as product liability, medical injury, data security, and responsibility attribution, and then evaluates the insufficiencies of current law, including its contradictions in allocating liability, continued frictions in data-compliance rules, and overall delays in regulatory adaptation. Upon this foundation, the article promotes a holistic regulatory strategy with four practical dimensions: clarifying rules on responsibility allocation, enhancing full-chain data governance, speeding up the formulation of dedicated laws, and building a co-governance model. Combined with each other, these four dimensions should provide a theoretical reference for regulating the development of medical AI in a dual-sided innovation-risk control.

KEYWORDS

Medical Artificial Intelligence; Legal Risks; Regulatory Strategies; Data Compliance

CITE THIS PAPER

Lianti Jiang. Legal Risks and Regulatory Strategies in the Clinical Application of Medical Artificial Intelligence. Science of Law Journal (2025) Vol. 4: 9-15. DOI: http://dx.doi.org/DOI: 10.23977/law.2025.040602.

REFERENCES

[1] Zhang, R. (2025). A study on the risks and regulatory mechanisms for medical institutions applying artificial intelligence technologies under the context of localized DeepSeek deployment. Health Development and Policy Research, 28(5), 493–500.
[2] Zhu, W., & Yan, Z. (2025). Ethical governance pathways of generative artificial intelligence in the German medical field and their implications. Medicine and Philosophy, 46(19), 27–31.
[3] Han, L., & Yue, Y. (2025). The occurrence logic and legal regulation of algorithmic discrimination in intelligent healthcare. Medicine and Society, 38(9), 47–53.
[4] Wang, Y., Ge, J., & Xu, Q. (2025). Legal liability and ethical challenges of artificial intelligence in medical decision-making: An analysis based on clinical scenarios. Journal of Naval Medical University, 46(8), 977–981.
[5] Bi, D., & Chang, L. (2025). Mechanisms for protecting patients' privacy rights in AI-based medical data analysis. Chinese Medical Ethics, 38(9), 1184–1190.

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