Artificial Intelligence in e-Health Framework, Volume 1

Artificial Intelligence in e-Health Framework, Volume 1 by Sudip Paul delivers a clear, practical roadmap for harnessing AI to transform modern healthcare. Engaging and accessible, this book captures the urgency of digital health adoption and translates complex AI concepts into actionable strategies for clinicians, administrators, policy makers, and developers.

Discover how machine learning, deep learning, natural language processing, and predictive analytics can be integrated into e-health systems to improve clinical decision support, patient monitoring, telemedicine, and population health management. Sudip Paul guides readers through implementation challenges—data governance, interoperability, privacy, and ethical considerations—offering pragmatic solutions that work in hospitals, primary care settings, and remote clinics across regions from Asia to Europe and North America.

Written for both technical and non-technical audiences, the volume balances theory with real-world relevance: deployment frameworks, workflow alignment, and measurable outcomes that healthcare leaders can apply immediately. Whether you are advancing a digital transformation in a metropolitan health system or designing scalable telehealth services for underserved communities, this book equips you with the language, tools, and confidence to make AI-driven change sustainable and patient-centered.

Packed with insights on regulatory landscapes, stakeholder engagement, and performance evaluation, this title is an indispensable reference for anyone shaping the future of e-health. Add Artificial Intelligence in e-Health Framework, Volume 1 to your professional library and lead the shift toward smarter, safer, and more equitable healthcare delivery. Order now to begin building AI solutions that deliver measurable clinical and operational value.

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