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Description

Artificial Intelligence (AI) has rapidly become a cornerstone of innovation in the healthcare industry, offering solutions that range from early diagnosis of diseases to virtual nursing assistants, precision medicine, and administrative automation. These applications are improving outcomes, lowering costs, and expanding access to care. However, as the use of AI expands, so do concerns around data privacy, algorithmic bias, patient consent, and regulatory compliance.

This session dives deep into both the "delights" and the "dangers" of AI in healthcare. On the positive side, we’ll explore how AI-powered tools are enabling faster, more accurate diagnoses, customizing treatment plans based on individual genetic profiles, and predicting patient deterioration before it becomes critical. Additionally, AI has begun easing operational burdens on healthcare systems, such as billing and scheduling.

But these technological advances come with trade-offs. We’ll examine risks such as algorithmic discrimination that can disproportionately affect minority and underrepresented patient groups, cybersecurity threats related to protected health information (PHI), and the lack of transparency in AI decision-making (black-box algorithms). Also, we'll unpack emerging regulations like the EU AI Act and how they intersect with HIPAA and other privacy laws.

This session aims to equip attendees with a foundational understanding of how AI can be leveraged responsibly in healthcare, highlight pitfalls to avoid, and encourage ongoing vigilance and governance. We will also discuss real-world examples and best practices for balancing innovation with risk.

Learning Objectives: -

Identify the top benefits and risks of using AI in healthcare
Understand how to assess AI tools for bias and compliance
Learn how to develop governance strategies around AI adoption
Gain familiarity with key regulations impacting AI in healthcare
Explore real-world examples to inform your organization’s approach.

Areas Covered in the Session:-

Overview of AI applications in clinical and operational healthcare
Benefits of AI in diagnosis, treatment, and patient care
Risks associated with data privacy, security, and compliance
Ethical concerns: bias, transparency, and patient autonomy
Regulatory landscape: HIPAA, GDPR, and the future of AI governance
Case studies of AI success and failure in healthcare settings
Best practices for responsible AI implementation.

Background:-

Artificial Intelligence (AI) is revolutionizing healthcare—from predictive diagnostics and robotic surgery to administrative efficiency and patient engagement. Yet, the same technologies introducing groundbreaking benefits also bring considerable ethical, security, and practical challenges. As AI continues to reshape clinical decision-making and patient outcomes, it is vital to critically examine both the advantages and the risks.

Why Should You Attend?

This session provides a balanced, insightful look at how AI is transforming healthcare and what it means for patients, clinicians, administrators, and security professionals. Whether you’re exploring AI's potential or navigating compliance, this session will equip you with the knowledge to embrace innovation responsibly and ethically.

Who Will Benefit?

Chief Medical Officers (CMOs)
Chief Information Security Officers (CISOs)
Healthcare Compliance Officers
Health IT Managers
Risk and Governance Professionals
Data Scientists and AI Developers
Clinicians and Medical Researchers.

The Dangers And Delights Of Artificial Intelligence In Healthcare

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