Challenges and solutions in securing AI algorithms in healthcare
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.
AI-Driven Healthcare Cybersecurity and Privacy;pp.35-65
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https://doi.org/10.4018/979-8-3373-2827-0.ch002 https://www.scopus.com/pages/publications/105007737793?origin=resultslist