PERSPECTIVE article
Front. Oncol.
Sec. Breast Cancer
A Nursing Perspective on Human-AI Collaboration in Personalized Breast Cancer Care Pathways
Jia-xin Zhang
Xue Zhao
Jihong Tao
De-chun Su
Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, China
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Abstract
The integration of artificial intelligence (AI) has shown strong performance in well-defined clinical tasks, particularly in reader studies and workflow simulations. Translation into routine clinical environments, however, depends on local integration strategies, threshold selection, and governance arrangements. This perspective article adopts a nursing science perspective to argue that human-AI collaboration represents more than a technological addition—it constitutes a fundamental shift toward a synergistically enhanced nursing practice. Central to this paradigm is the effective integration of nursing expertise with algorithmic capabilities throughout all stages of care. When appropriately implemented and supervised, such integration has the potential to enhance both precision and efficiency in nursing practice. Importantly, it should be carried out in a way that preserves core nursing values, including patient-centered care, respect for individual dignity, and the integrity of therapeutic relationships. The proposed framework establishes a conceptual foundation intended to support the design of ethically aligned and clinically relevant human-AI systems. It further aims to guide the evolution of nursing practice within personalized breast cancer care.
Summary
Keywords
artificial intelligence, breast cancer, Digital Health, Human-machine collaboration, nursing perspective, Patient-Centered Care
Received
09 January 2026
Accepted
19 February 2026
Copyright
© 2026 Zhang, Zhao, Tao and Su. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: De-chun Su
Disclaimer
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