Practical Artificial Intelligence for Internet of Medical Things 1st Edition

Grab the future of connected healthcare with Practical Artificial Intelligence for Internet of Medical Things, 1st Edition by Ben Othman Soufiene. This concise, hands-on guide bridges cutting‑edge AI techniques and real-world Internet of Medical Things (IoMT) deployments, making advanced technology immediately useful for clinicians, engineers, and health-tech leaders.

Inside you’ll find clear, applied explanations of machine learning and deep learning models tailored to medical sensors, wearable devices, and remote monitoring systems. The book walks through end-to-end IoMT architectures, edge and cloud integration, data preprocessing, model selection, and performance evaluation — all focused on clinical relevance and patient safety. Practical case studies and implementation strategies highlight predictive diagnostics, anomaly detection, personalized care pathways, and telemedicine workflows that make a measurable impact on outcomes.

Designed for practitioners across hospitals, research labs, startups, and academic settings worldwide, this edition also tackles essential non‑technical topics: security and privacy best practices, regulatory considerations, and deployment challenges unique to healthcare environments. Readers will gain the confidence to move from prototypes to production-ready solutions that comply with real-world constraints.

If you want a pragmatic, professionally written roadmap to applying AI within IoMT ecosystems—grounded in examples and focused on clinical value—this book is an indispensable resource. Ideal for data scientists, biomedical engineers, clinicians, and healthcare administrators aiming to innovate responsibly in connected care. Order your copy of Practical Artificial Intelligence for Internet of Medical Things today and start turning data into safer, smarter patient care.

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