Journal of Clinical Oncology & Advanced Therapy

Abstract

Artificial intelligence has become an influential component of contemporary oncology, contributing to cancer diagnosis, treatment planning, risk prediction, and clinical decision support. Despite these advances, the integration of intelligent systems into healthcare raises important ethical, epistemological, and governance challenges. This study examines the conditions necessary for the responsible incorporation of artificial intelligence into oncology through a human-centered framework that emphasizes trust, ethical governance, and human accountability. The research argues that the effectiveness and legitimacy of artificial intelligence depend not solely on algorithmic accuracy but on its ability to operate within institutional structures that preserve professional responsibility, patient autonomy, and public trust. The study develops an interdisciplinary analysis that integrates medical ethics, philosophy of technology, healthcare governance, and artificial intelligence studies. It examines the epistemological distinction between human interpretive intelligence and algorithmic predictive intelligence and proposes that sustainable oncology requires a collaborative relationship between these complementary forms of knowledge. To advance this argument, the research introduces three original conceptual contributions. The first is Algorithmic Trust Ecology, which conceptualizes trust as a dynamic system of relationships among patients, clinicians, institutions, and intelligent technologies.

The second is Human Accountability Preservation, which maintains that responsibility for medical decisions must remain attached to human actors regardless of algorithmic involvement. The third is Epistemic Symbiosis in Oncology, which describes a cooperative knowledge partnership between artificial intelligence and clinical expertise. The study concludes that artificial intelligence should function as a decision-support partner rather than an autonomous authority. The future of intelligent oncology depends on governance frameworks that combine transparency, accountability, trust, and ethical oversight while preserving the central role of human judgment. Such an approach provides a foundation for integrating technological innovation into cancer care without compromising the ethical principles that sustain responsible medical practice.