Course Overview
Learning Objectives
- Understand the principles and importance of Explainable AI (XAI) in regulated industries.
- Apply XAI techniques to interpret and validate AI models used in drug discovery, clinical trials, and patient diagnostics.
- Evaluate the transparency, fairness, and trustworthiness of AI decisions in critical life science applications.
- Learn how XAI can significantly enhance cybersecurity by aiding in the detection of hidden biases, data poisoning, or malicious injections within AI models, thereby improving the resilience of AI systems against sophisticated cyber manipulations.
- Discuss the regulatory requirements and best practices for achieving explainability in AI for healthcare and biotech.
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):