Mathematical Modeling and AI-Driven Computational Techniques for Epidemiology and Disease Dynamics offers a comprehensive exploration of innovative methodologies at the intersection of mathematics, biology, and medicine. This book delves into advanced mathematical modeling, artificial intelligence, and computational intelligence, providing essential tools for understanding and managing complex disease dynamics. Covering a wide range of topics, including fractional-order modeling, optimal control strategies, and privacy-preserving technologies, it addresses critical challenges in public health and healthcare systems. With contributions from leading experts, this volume bridges theoretical advancements and practical applications, making it an invaluable resource for researchers, healthcare professionals, and academics seeking interdisciplinary solutions to global health issues. - Presents advanced modeling techniques like fractional-order systems, stochastic analysis, and deep learning frameworks applied to real-world problems such as breast cancer, dengue, HBV, LSD, and COVID-19- Provides practical solutions for disease control strategies, viscoelastic tissue modeling, and healthcare data security, fostering interdisciplinary applications of computational intelligence- Offers a forward-looking perspective on the application of computational intelligence in healthcare, emphasizing sustainable monitoring and mitigation strategies

Mathematical Modeling and AI-Driven Computational Techniques for Epidemiology and Disease Dynamics offers a comprehensive exploration of innovative methodologies at the intersection of mathematics, biology, and medicine. This book delves into advanced mathematical modeling, artificial intelligence, and computational intelligence, providing essential tools for understanding and managing complex disease dynamics. Covering a wide range of topics, including fractional-order modeling, optimal control strategies, and privacy-preserving technologies, it addresses critical challenges in public health and healthcare systems. With contributions from leading experts, this volume bridges theoretical advancements and practical applications, making it an invaluable resource for researchers, healthcare professionals, and academics seeking interdisciplinary solutions to global health issues. - Presents advanced modeling techniques like fractional-order systems, stochastic analysis, and deep learning frameworks applied to real-world problems such as breast cancer, dengue, HBV, LSD, and COVID-19- Provides practical solutions for disease control strategies, viscoelastic tissue modeling, and healthcare data security, fostering interdisciplinary applications of computational intelligence- Offers a forward-looking perspective on the application of computational intelligence in healthcare, emphasizing sustainable monitoring and mitigation strategies

Mathematical Modeling and AI-Driven Computational Techniques for Epidemiology and Disease Dynamics offers a comprehensive exploration of innovative methodologies at the intersection of mathematics, biology, and medicine. This book delves into advanced mathematical modeling, artificial intelligence, and computational intelligence, providing essential tools for understanding and managing complex disease dynamics. Covering a wide range of topics, including fractional-order modeling, optimal control strategies, and privacy-preserving technologies, it addresses critical challenges in public health and healthcare systems. With contributions from leading experts, this volume bridges theoretical advancements and practical applications, making it an invaluable resource for researchers, healthcare professionals, and academics seeking interdisciplinary solutions to global health issues. - Presents advanced modeling techniques like fractional-order systems, stochastic analysis, and deep learning frameworks applied to real-world problems such as breast cancer, dengue, HBV, LSD, and COVID-19- Provides practical solutions for disease control strategies, viscoelastic tissue modeling, and healthcare data security, fostering interdisciplinary applications of computational intelligence- Offers a forward-looking perspective on the application of computational intelligence in healthcare, emphasizing sustainable monitoring and mitigation strategies