Inbum Lee, Minsoo Joo, Jong-Moon Chung
Advances in T cell-based immunotherapy for cancer treatment, coupled with breakthroughs in artificial intelligence (AI), have led to a surge in AI-driven analysis and prediction algorithms. However, significant challenges remain in translating these computational methods into clinical practice. This paper reviews the technical trends in AI-based approaches for T cell-based immunotherapy, identifies key limitations and potentials for improvement, and proposes future research directions to bridge the gap between computational methods and clinical implementation.