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AI in Clinical Decision-Making in Rare Events Essentials
"AI in Clinical Decision-Making in Rare Events Essentials" explores how AI assists clinicians in low-frequency, high-impact healthcare scenarios. Participants study machine learning for diagnostics and anomaly detection. A focus on cybersecurity emphasizes the protection of sensitive patient data and medical AI models from tampering. Securing these systems ensures trustworthy decision support in life-critical contexts.
Course Overview
None
Learning Objectives
- Understand the principles of AI in clinical decision-making for rare events.
- Analyze the challenges of using AI for rare event diagnosis and treatment.
- Evaluate the benefits and limitations of AI in improving clinical outcomes.
- Identify the key considerations for developing and validating AI-driven clinical decision support systems.
- Discuss the ethical and regulatory aspects of AI in healthcare.
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):
Competency Areas
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.