Mathematical Modeling and AI-Driven Computational Techniques for Epidemiology and Disease Dynamics

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Mathematical Modeling and AI-Driven Computational Techniques for Epidemiology and Disease Dynamics

Jose, Sayooj Aby (EDT)/ C.R., Jisha (EDT)/ Boubaker, Olfa (EDT)

ウェブストア価格 ¥39,029（本体¥35,481）
Academic Press Inc（2026/02発売）
外貨定価 US$ 180.00
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製本 Paperback:紙装版/ペーパーバック版／ページ数 410 p.
言語 ENG
商品コード 9780443332340
DDC分類 614.40151

Full Description

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.

Part I: Classical and Fractional Approaches to Infectious Disease Modeling
1. Mathematical and AI-Based Approaches in Epidemiology: Foundations and Frontiers
2. Comparative Numerical Methods for Infectious Disease Dynamics: Application to SEIR-type Models
3. Fractional Order Modeling and Stability Analysis of Vector-Borne Diseases: Application to Japanese Encephalitis Transmission
4. Optimal Control of Infectious Diseases Using Fractional Calculus: Application to Dengue Control via Atangana-Baleanu Model

Part II: Artificial Intelligence and Advanced Modeling in Epidemiology
5. Eco-Epidemiological Modeling with Memory Effects: Application to Fear, Quarantine, and Prey-Predator Interactions via Mittag-Leffler Kernel
6. Stochastic Analysis of Epidemic Models Under Random Perturbations: Application to SIR and SIRS Dual Epidemics
7. Deep Learning-Based Optimal Control Frameworks in Epidemiology: Application to Dengue Transmission Prediction and Control
8. AI-Driven Fractional Order Models for Emerging Viral Epidemics: Application to Oropouche Virus Outbreak Forecasting

Part III: Mathematical, Statistical, and AI-Based Models in Biomedicine and Healthcare
9. Explainable AI and Computational Intelligence in Healthcare: Application to Clinical Decision Support and Personalized Medicine
10. Soft Computing Models of Biological Tissue Dynamics: Application to Viscoelastic Behavior of Biological Tissues
11. Mathematical Modeling of Cancer Progression: Application to Ductal Carcinoma of the Breast
12. Modeling Immune Response and Antiviral Therapy Dynamics: Application to HBV Infection in Hepatic and Extrahepatic Sites
13. Statistical Modeling and Evaluation of Polyherbal Formulations: Application to Management of Diabetic Foot Ulcers
14. Conclusion | Prospects in computational epidemiology: challenges and emerging directions