Applications of Artificial Intelligence in Cancer Precision and Personalized Medicine

Abstract

Artificial Intelligence (AI), as a rapidly evolving technology, is fundamentally transforming the diagnosis and treatment of cancer. This article systematically discusses the research and application progress of AI in key areas such as medical image analysis, genomic data interpretation, personalized treatment design, and clinical decision support. In medical imaging, AI, powered by deep learning, significantly enhances the sensitivity and accuracy of tumor detection in CT, MRI, and other scans, reduces human error, and enables multi-lesion monitoring and dynamic tumor tracking. In genomic data interpretation, AI can accurately identify cancer-related driver mutations and biomarkers, accelerating early screening and risk prediction, and providing a scientific basis for personalized treatment plans. Meanwhile, AI's application in drug discovery and cancer immunotherapy continues to expand, improving drug candidate prediction efficiency and accurately predicting immune therapy responses to optimize treatment combinations. AI-assisted clinical decision systems integrate multimodal data to provide individualized treatment suggestions, facilitating the transition of cancer therapy from experience-based to data-driven methods. Although challenges such as data privacy, model interpretability, and ethical concerns remain, AI holds great promise in cancer precision medicine and is poised to become a vital component of future oncology care.