Deep Learning in Internet of Things for Next Generation Healthcare 1st Edition

Deep Learning in Internet of Things for Next Generation Healthcare (1st Edition) by Lavanya Sharma and Pradeep Kumar Garg offers a clear, practical roadmap for integrating AI-powered learning with connected medical devices to transform patient care worldwide.

Imagine faster diagnoses, continuous remote monitoring, and personalized treatment plans driven by real-time data from wearable sensors and hospital IoT networks. This book captures that promise—explaining deep learning architectures, edge and cloud deployments, predictive analytics, and privacy-aware design in accessible language for professionals across healthcare, engineering, and research.

Readers gain actionable insights into:
– Building robust IoT pipelines for remote patient monitoring and telemedicine.
– Applying convolutional and recurrent networks to medical signals and imaging.
– Deploying models at the edge to reduce latency and protect sensitive health data.
– Case-driven examples showing practical deployment challenges and solutions across global healthcare settings, including India, Europe, North America, and Asia-Pacific.

Written for graduate students, data scientists, biomedical engineers, clinicians, and IT leaders, the book balances theory with industry-relevant guidance—making it ideal for those designing next-generation healthcare systems or pursuing applied research in AI and IoT. Practical, forward-looking, and globally relevant, it emphasizes ethical considerations, regulatory awareness, and scalability.

Secure your copy to stay ahead in the evolving intersection of artificial intelligence and connected healthcare. Whether you’re building smart hospitals, remote monitoring platforms, or predictive health analytics, this authoritative guide will help you turn data into better patient outcomes. Purchase now to lead the future of digital health.

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