Data Fusion Techniques and Applications for Smart Healthcare 1st Edition

Capture the future of clinical decision-making with Data Fusion Techniques and Applications for Smart Healthcare, 1st Edition by Amit Kumar Singh and Stefano Berretti. This indispensable volume delivers a clear, practical roadmap for integrating diverse medical data sources to build robust, intelligent healthcare systems.

Explore how advanced data fusion—combining signals from wearables, medical imaging, electronic health records, and IoT devices—unlocks richer diagnostics, accurate patient monitoring, and timely interventions. Written for data scientists, clinicians, biomedical engineers, and healthcare leaders, the book balances rigorous methodology with real-world case studies and actionable insights. Core topics include sensor-level fusion, decision-level integration, machine learning pipelines, uncertainty handling, and privacy-aware architectures tailored for clinical environments.

Whether you’re deploying predictive analytics in a smart hospital in Europe, building remote-monitoring solutions for rural clinics in Asia, or scaling population health initiatives in North America, this guide translates complex theory into deployable strategies. Learn best practices for data preprocessing, model fusion, interoperability, and ethical considerations that ensure safe, effective adoption across global healthcare systems.

Readable, authoritative, and forward-looking, Data Fusion Techniques and Applications for Smart Healthcare positions you at the intersection of technology and care delivery. Enhance patient outcomes, reduce false alarms, and accelerate research with approaches that matter. Add this essential reference to your professional library and start transforming fragmented health data into actionable intelligence today.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.