Full Description
This textbook provides a comprehensive introduction to intelligent systems, integrating foundational theories, learning paradigms, and practical applications with a specific emphasis on biomedical and healthcare domains. The book combines theoretical foundations with real-world applications and serves as an essential resource for understanding intelligent systems and their transformative role in modern AI-driven biomedical innovations. Ethical and regulatory challenges specific to AI in biomedicine are also discussed. Practice problems and exercises complete this valuable resource for students, researchers, and professionals working in this field.
Contents
Theories and Algorithms: Introduction to Intelligent Systems.- Supervised Learning Techniques.- Advanced Supervised Learning.- Unsupervised Learning Techniques.- Advanced Unsupervised Learning.- Perceptrons and Multilayer Perceptrons (MLPs).- Fundamentals of Neural Networks.- Advanced Network Classifications.- Fuzzy Systems and Their Applications.- Modern AI and Emerging Technologies.- Applications of Intelligent Systems in Biomedicine: AI in Medical Imaging and Diagnostics.- Intelligent Systems in Medical Device Performance Assessment.- Diagnostic Support Systems and Clinical Decision Making.- AI-Driven Personalized Medicine and Drug Discovery.- Wearable Biosensors and Remote Health Monitoring.- Robotics and AI in Surgery and Rehabilitation.- AI in Biomedicine: Ethical, Regulatory, and Future Considerations.- Review & Practice Problems: Summary of Key Concepts.- Practice Problems and Exercises.
