Course Prerequisites:
Basic digital literacy (e.g., using EHRs, accessing online platforms) Clinical background (MBBS, MD, DO, RN, NP, PA, etc.) No programming or data science background required
Modules:
Module 1: What is AI in Medicine?
1.1 Understanding AI Fundamentals
1.2 Clinical Relevance of AI
Module 2: AI in Diagnostics & Imaging
2.1 Deep Learning in Clinical Imaging
2.2 Interpreting and Using AI Outputs
Module 3: Predictive Analytics & Clinical Decision Support
3.1 Building Predictive Risk Models
3.2 Implementing Clinical AI Alerts
Module 4: NLP and Generative AI in Clinical Use
4.1 Foundations of NLP and LLMs
4.2 Using ChatGPT in Medicine
Module 5: Predictive Analytics & Clinical Decision Support
5.1 Ethical and Equitable AI Use
5.2 Regulation and Responsibility
Module 6: Evaluating AI Tools in Practice
6.1 Metrics That Matter to Clinicians
6.2 Assessing AI Products and Vendors
Module 7: Implementing AI in Clinical Settings
7.1 Integrating AI into Workflows
7.2 Team Collaboration and Monitoring
Module 8: The Future of AI & Your Role
8.1 Emerging Trends in Medical AI
8.2 Becoming an AI Leader in Medicine