Book overview
Healthcare data is one of the most sensitive and valuable digital assets, making the healthcare sector a frequent target for cyberattacks and data breaches. When breaches occur, it is not only medical records that are exposed, but also highly personal information, including mental health records and other sensitive data that can leave patients particularly vulnerable. As a result, the security of healthcare systems has become an increasingly important concern. At the same time, artificial intelligence is being rapidly integrated across healthcare operations, creating new opportunities to strengthen cybersecurity applications within the healthcare domain. Despite these advances, research remains fragmented, highlighting the need for a centralized body of knowledge that provides practical guidance on implementing AI-driven cybersecurity solutions within healthcare administration systems. Cybersecurity, AI Collaboration, and Software Practice for Healthcare provides a comprehensive and multidisciplinary exploration of the intersection between cybersecurity, AI collaboration, and software practice in healthcare. This book bridges the gap between technical innovation and secure, responsible implementation by highlighting strategies, frameworks, and case studies that ensure the safety and reliability of AI-enabled healthcare systems. Covering topics such as data poisoning in AI-driven medical imaging software, blockchain technology in medicine, and security of image transmission, this book is an essential academic resource for graduate and doctoral students, healthcare professionals and administrators, software developers and AI practitioners, regulators, policymakers, and more.
