Artificial Intelligence in Medical Software
Book Details
Format
Hardback or Cased Book
ISBN-10
3032108071
ISBN-13
9783032108074
Publisher
Springer Nature Switzerland AG
Imprint
Springer Nature Switzerland AG
Country of Manufacture
GB
Country of Publication
GB
Publication Date
May 2nd, 2026
Print length
442 Pages
Product Classification:
Biomedical engineeringBiomedical engineering / Medical engineeringEmbedded systems
Ksh 19,800.00
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Unlock the future of healthcare innovation with this comprehensive guide to AI and machine learning in medical software. Designed for engineers, data scientists, and healthcare leaders, this book provides a practical roadmap for developing safe, effective, and compliant AI/ML-driven medical devices. From foundational principles to advanced deployment, including Software in Medical Devices (SiMD) and Software as a Medical Device (SaMD), this book covers everything you need to know. Explore a unique end-to-end development methodology tailored for AI-enabled solutions, cloud architectures, and regulated healthcare environments. Discover how to streamline product releases, navigate privacy and security mandates, and master global medical device regulations—all this while accelerating time to market with real-world strategies and tools. Hands-on projects and exclusive case studies, such as Apple’s Sleep Apnea Notification and Notal Vision’s Home OCT system, provide actionable insights from the cutting edge of AI-powered diagnosis and care. Whether you’re just starting or scaling enterprise-grade AI, this book teaches you how to leverage tomorrow’s innovations, including Generative AI, federated learning, edge deployment, and cloud-native best practices. Keep usability, trust, and safety at the heart of your solutions. This book bridges the technical and clinical worlds, making it your indispensable companion for building the future of intelligent healthcare. Describes each stage of AI/ML-enabled medical device development, covering both regulatory and technical requirements;Illustrates how AI/ML-enabled device development differs from traditional software development in medical devices;Includes strategies for addressing common challenges during development and regulatory review.
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