Artificial Intelligence in Oncology: From Image Recognition to Molecular Precision Therapies

Abstract

Artificial Intelligence (AI) is revolutionizing oncology by transforming cancer detection, diagnosis, and treatment into a data-driven, precision medicine paradigm. This review explores the multifaceted applications of AI across oncological imaging, tumor genomics, liquid biopsy, tumor microenvironment modeling, and therapeutic strategies. We highlight breakthroughs in AI-assisted radiomics and digital pathology, which now match or surpass human expert performance in specific diagnostic tasks. The integration of multi-omics data through graph neural networks and reinforcement learning enables personalized therapy prediction and adaptive treatment optimization. Emerging technologies, such as AI-enhanced nanoparticle design and quantum computing, promise to further accelerate drug discovery and radiotherapy planning. Ethical considerations, explainable AI, and federated learning frameworks are discussed to address challenges in bias, transparency, and global equity. By bridging computational innovation with clinical practice, AI is poised to democratize precision oncology, improve survival outcomes, and redefine cancer care worldwide.