Revolutionizing Cancer Therapy: The Role of Artificial Intelligence in Enhancing Treatment Efficacy

The World Health Organization (WHO) has identified cancer as a major cause of death, accounting for approximately 16 percent of global deaths. The Cancer-Moonshot initiative aims to reduce cancer-related mortality by 50 percent over the next 25 years and improve the lives of those affected. Early detection and appropriate treatment are crucial in reducing cancer mortality rates, with high cure probabilities for cancers like breast and cervical cancer when treated early. The integration of artificial intelligence (AI) into cancer research shows promising outcomes, addressing challenges where traditional medical approaches fall short. AI provides tools and platforms that enhance our understanding and combat this life-threatening disease. AI-based systems assist pathologists in more accurate and consistent cancer diagnosis, reducing errors. Predictive AI models identify risk factors and estimate the likelihood of cancer development. Leveraging big data with AI enables the development of personalized cancer treatments, minimizing side effects compared to generalized therapies. However, for AI tools to effectively save lives, they must be accessible and understandable to biologists, oncologists, and medical researchers. This paper explores the current trends, challenges, and future directions of AI in cancer research, aiming to provide valuable insights for both medical and technical experts in the field.