AI Ethics and Explainable AI (XAI) in Healthcare
Ensuring Ethical and Transparent AI in Healthcare: From Fairness to Explainability
Skills you will gain:
This program emphasizes the ethical considerations of using AI in healthcare, such as fairness, bias, accountability, and patient privacy. Additionally, it covers Explainable AI (XAI) methodologies that ensure transparency, allowing healthcare professionals and patients to understand the decisions made by AI systems. The program integrates hands-on experience with case studies of AI implementations in healthcare, addressing ethical dilemmas and regulatory frameworks.
Aim: To explore the intersection of AI ethics and Explainable AI (XAI) in the healthcare industry. This program is designed to equip PhD scholars, academicians, and healthcare professionals with knowledge of ethical challenges and explainability in AI-powered healthcare applications, ensuring trust, transparency, and fairness in medical AI systems.
Program Objectives:
- Understand key ethical concerns in AI systems for healthcare.
- Master techniques in Explainable AI (XAI) to ensure transparency in medical AI applications.
- Explore real-world case studies of ethical AI in healthcare.
- Learn about regulatory frameworks governing AI in healthcare.
- Gain hands-on experience in building explainable AI models for healthcare.
What you will learn?
- Introduction to AI Ethics in Healthcare
- Overview of ethical challenges in healthcare AI applications
- Regulatory considerations and compliance (HIPAA, GDPR)
- Key Ethical Issues in AI
- Bias, fairness, transparency, and accountability in healthcare AI
- Addressing bias in AI-based medical decisions
- Explainable AI (XAI) for Healthcare
- Importance of explainability in clinical AI systems
- Techniques for XAI (LIME, SHAP, counterfactual explanations)
- Case Studies: AI Ethics in Healthcare
- Real-world examples of AI systems in healthcare
- Ethical failures and success stories in healthcare AI
- Regulatory Frameworks and Legal Considerations
- Overview of regulations governing AI in healthcare
- Future trends in AI governance
- Hands-on Session: Building Explainable Healthcare AI
- Implementation of XAI techniques in AI models for healthcare
- Debugging and explaining AI-driven healthcare decisions
Intended For :
AI researchers, healthcare professionals, ethicists, legal experts, and academicians focusing on healthcare AI.
Career Supporting Skills