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Artificial Intelligence in Healthcare Information Systems: Security and Privacy Challenges
University of New York Tirana, Albania.ORCID iD: 0000-0002-8260-2392
University of Tirana, Albania.ORCID iD: 0000-0002-0684-7590
Linnaeus University, Faculty of Technology, Department of Informatics.ORCID iD: 0000-0001-7520-695x
Norwegian University of Science and Technology, Norway.ORCID iD: 0000-0001-6189-1976
2025 (English)Collection (editor) (Other academic)
Sustainable development
SDG 3: Ensure healthy lives and promote well-being for all at all ages
Abstract [en]

"Artificial Intelligence (AI) in Healthcare Information Systems: Security and Privacy Challenges” offers a deep dive into the integration of AI in healthcare, with a primary focus on addressing the significant security and privacy concerns that arise in this domain. The chapters in this book highlight the transformative potential of AI in diagnosing and predicting diseases, as well as its impact on fields like fetal medicine, but places special emphasis on the need for robust encryption, data protection techniques, and ethical considerations to safeguard sensitive healthcare data. The book also explores global case studies, from India to Kazakhstan, outlining the challenges and prospects of AI adoption in diverse healthcare settings. Readers will gain insights into AI's role in improving patient outcomes while navigating the complexities of data privacy and security. The book is a valuable resource for healthcare professionals, technologists, and policymakers who are focused on implementing AI-driven solutions securely and ethically in healthcare systems.

Place, publisher, year, edition, pages
Switzerland: Springer Nature, 2025, 1.
Series
Information Systems Engineering and Management, ISSN 3004-958X, E-ISSN 3004-9598
Keywords [en]
Data Engineering, AI in Healthcare, Healthcare Data Security, Patient Privacy, Ethical Considerations, Regulatory Compliance, AI Model Security, Data Encryption and Protection, Trust and Transparency, Interoperability, Data Sharing
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-134304ISBN: 9783031844034 (print)ISBN: 9783031844041 (electronic)OAI: oai:DiVA.org:lnu-134304DiVA, id: diva2:1924326
Available from: 2025-01-04 Created: 2025-01-04 Last updated: 2025-01-10Bibliographically approved

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https://link.springer.com/book/9783031844034

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Dalipi, Fisnikf

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CiteExportLink to record
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