Digital Medical Twins for Personalized Healthcare

Digital Medical Twins for Personalized Healthcare: Generative AI and Multi-Modal Approaches for Predictive Diagnostics and Precision Medicine presents a rigorous, evidence-based framework for building patient-specific digital replicas that support clinical decision-making and research innovation. The field integrates electronic health records, imaging, genomics, and continuous wearable data into dynamic models that simulate disease trajectories and treatment responses. Readers confront a evolving landscape of AI methods, privacy requirements, and regulatory expectations; this book offers a coherent, practical reference designed for scientists, and health-system professionals seeking to translate digital twins from concept to care delivery.

• Provides foundational concepts and practical guidance for digital medical twins
• Integrates generative and multi-modal AI to enhance patient data modeling
• Addresses explainability, privacy, and regulatory alignment for clinical data use
• Offers cross-disciplinary case studies across cardiology, oncology, neurology, and preventive care