Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Koshy, Jabin Shiji Title A name given to the resource Challenges and solutions in securing AI algorithms in healthcare Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived AI-Driven Healthcare Cybersecurity and Privacy;pp.35-65 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-2827-0.ch002" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-2827-0.ch002</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105007737793?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105007737793?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Koshy J.S., Christ University, India Description An account of the resource The paper discusses existing challenges that, based on the legal framework, the regulatory change must affect in order to ensure interest coverage in the health sector. Massive opportunities lie in the role that AI plays in healthcare in the forms of diagnostics and personalized care, while major challenges arise. AI models like machine learning, deep learning, and neural networks have improved healthcare outcomes, but they raise concerns on the privacy of patient data, explainability, and cyber threats such as adversarial attacks. Sensitive data must be protected for patients to trust AI-driven diagnosis. Bias in algorithms, the obtaining of informed patient consent, and the accountability of the AI decisions are some ethical and regulatory issues. Regulations like HIPAA(Health Insurance Portability and Accountability Act) and GDPR(General Data Protection Regulation) are the most important while considering data protection.This includes better encryption and anonymisation of patient data, interpretable models, and stronger defences against cyber-attacks. 2025, IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833732829-4; 979-833732827-0; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online