Description
Book SynopsisPart I: Foundations of Generative AI in Medicine.- Introduction to Generative AI in Clinical Practice.- Transformer Architectures & Self-Attention: How AI Thinks.- Core Technologies: NLP, Convolutional Neural Networks, and Retrieval-Augmented Generation.- Prompt Engineering for Clinicians: From Basics to Advanced Techniques.- Limitations, Bias, and Risk Management in AI Outputs.- Ethics, Accountability, and Human Oversight in Generative AI.- Specialty Deep Dives: Imaging, Patient Education, and RAG Applications.- Generative AI in Primary Care: Opportunities and Challenges.- Part II: Integrating AI into Clinical Workflows.- Securing Early Support: Stakeholder Mapping & Buy-In.- Anticipating Resistance: Safeguards, Errors, and Prompt Refinement.- Simulation Exercises: You Are the CMIO Role-Plays.- Feedback Loops & Continuous Learning: The AI Rounds Model.- Part III: Capstone & Application.- Mini AI Journal Club: Peer-Led Case Studies & Lessons Learned.- Execution, Analysis & Iteration: PromptReviewRevise with QI Methods.- Reporting, Scale-Up & Sustainability: Communicating and Governing AI Projects.- Part IV: Professional Growth & Lifelong AI Integration.- Next StepsProfessional Growth & Lifelong AI Integration.
