Leveraging AI in Medical Engineering for Targeted Cancer Therapy Delivery

Abstract

Abstract: This paper explores the utilization of artificial intelligence (AI) in medical engineering to optimize targeted cancer therapy delivery. Targeted cancer therapy has emerged as a promising approach for improving treatment outcomes and reducing side effects by selectively targeting cancer cells while sparing healthy tissues. AI-driven technologies offer novel opportunities to enhance the precision and efficacy of targeted therapy delivery through personalized treatment planning, real-time monitoring, and adaptive treatment strategies. By leveraging AI algorithms for data analysis, predictive modeling, and decision support, medical engineers can optimize drug dosing, treatment schedules, and drug delivery systems tailored to individual patient characteristics and tumor biology. This paper reviews recent advancements in AI-driven medical engineering techniques for targeted cancer therapy delivery, including image-guided drug delivery, nanoparticle-based drug delivery systems, and intelligent drug release mechanisms. Additionally, challenges such as data integration, model interpretability, and regulatory compliance are discussed, along with future directions for research and clinical implementation. By harnessing the power of AI in medical engineering, targeted cancer therapy delivery can be optimized, leading to improved treatment outcomes, reduced toxicity, and enhanced patient quality of life in the fight against cancer.