From Code to Care: A Practical Framework for Ethical Artificial Intelligence Integration in Clinical Settings

ABSTRACT Artificial intelligence (AI) is poised to transform oncology by enhancing diagnostic accuracy, enabling treatment personalization, and improving operational efficiency. However, its rapid deployment introduces ethical concerns related to transparency, bias, clinical oversight, and patient safety. These concerns are especially critical in cancer care, where decisions often carry life-altering consequences. This review presents a practical framework for the ethical integration of AI into oncology practice. Grounded in patient-centered values and real-world clinical implementation, it offers seven guiding principles: prioritizing patient well-being, respecting clinical context, ensuring transparency, upholding clinical quality, maintaining ethical vigilance, reinforcing human oversight, and empowering clinicians. The framework is illustrated with oncology-relevant examples, including digital pathology, radiomics, and multi-omics data interpretation. Governance recommendations address data privacy, digital infrastructure, training, and oversight. By embedding ethics from design through deployment, AI can serve as a trusted partner in delivering equitable, safe, and human-centered cancer care.