This book explores how the human microbiome interacts with the immune system to influence cancer development, progression, and treatment response. It emphasizes the role of the microbiome-immune axis as a critical factor in precision cancer therapy. By integrating artificial intelligence and machine learning approaches, the book demonstrates how complex biological data from microbiome profiles, immune markers, and clinical outcomes can be analyzed to optimize personalized cancer treatments. It discusses AI-driven models for predicting immunotherapy efficacy, reducing adverse effects, and identifying novel therapeutic targets. Overall, the book bridges microbiology, immunology, oncology, and data science, offering a forward-looking framework for next-generation precision oncology based on microbiome-informed and AI-supported decision-making.
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