HUMAN–ARTIFICIAL INTELLIGENCE COLLABORATION IN ONCOLOGY: BUILDING TRUSTWORTHY CLINICAL INTELLIGENCE SYSTEMS

Abstract

Human–artificial intelligence (AI) collaboration is redefining precision oncology by establishing trustworthy clinical intelligence systems that combine computational power with clinician expertise to improve cancer diagnosis, therapeutic decision-making, disease monitoring, and personalized patient care. Rather than replacing healthcare professionals, modern AI systems function as collaborative partners that augment multidisciplinary oncology teams through integration of radiological imaging, digital pathology, genomics, transcriptomics, proteomics, metabolomics, epigenomics, spatial biology, laboratory biomarkers, circulating tumor DNA, wearable physiological monitoring, electronic health records, biomedical literature, and longitudinal clinical outcomes. Recent advances in foundation AI models, multimodal transformer architectures, graph neural networks, self-supervised learning, reinforcement learning, and generative artificial intelligence have enabled comprehensive multimodal reasoning across heterogeneous biomedical data while supporting explainable, adaptive, and continuously learning clinical decision support. Emerging technologies including multimodal large language models, federated learning, retrieval-augmented generation, agentic AI, digital twins, cloud-native healthcare platforms, and digital health ecosystems further strengthen collaborative intelligence by enabling transparent, privacy-preserving, evidence-based, and human-centered oncology practice. Despite remarkable technological progress, successful implementation requires overcoming challenges related to explainability, clinical validation, interoperability, algorithmic bias, cybersecurity, regulatory governance, clinician trust, patient acceptance, and ethical deployment. This review provides a comprehensive overview of human–AI collaboration in oncology, emphasizing the development of trustworthy clinical intelligence systems capable of supporting adaptive precision medicine and personalized therapeutics.