886: The Physician’s Guide to Advanced Artificial Intelligence: From Prompting to Practice

Saturday, November 14, 2026
1:15 pm - 4:15 pm

Room: EXHALL-D5

Chairs: Sergio Haimovich

Faculty:

Description: This course explores the practical and professional applications of Artificial Intelligence (AI) in academic medicine and daily clinical workflows. Designed specifically for physicians, surgeons, and medical educators, the program shifts the paradigm of AI from a simple search engine to a highly controlled, probabilistic tool.

As the medical field rapidly evolves, uncontrolled AI can produce "beautiful, confident, wrong answers," making this training crucial for clinical accuracy and patient safety.

Participants will learn the science of "Prompt Engineering," moving beyond basic interactions to programing AI systems using a structured 6-layer framework.

Throughout the course, learners will gain hands-on experience utilizing cutting-edge AI tools for text synthesis, literature review, automated workflows, and multimodal content creation, including images and video.

By the end of the course, participants will be able to transform AI into a "disciplined PhD-level assistant," accelerating their research analysis and elevating their academic presentations while maintaining rigorous scientific oversight.

Learning Objectives: At the end of this course, the participant will be able to:

1. Understand the foundational mechanisms of AI prompt engineering as a programming interface for probabilistic systems and learn to design professional, 6-layer prompts that explicitly define role, objective, context, rules, format, and evaluation criteria;
2. Apply temperature controls and chain-of-thought instructions to minimize AI hallucinations and prevent logical errors in medical contexts and critically analyze AI-generated outputs for clinical accuracy, ensuring the physician remains the ultimate authority on patient safety and guidelines;
3. Integrate major Large Language Models (LLMs) and specialized research tools (e.g., ChatGPT, Gemini, Perplexity, Consensus) into literature review workflows and Implement AI-driven platforms (like Gamma and NotebookLM) to structure and design clear, high-impact academic presentations;
4. Evaluate and select appropriate multimodal AI applications (text-to-image, text-to-video) to create compelling visual metaphors for medical education; and
5. Design automated daily routines to efficiently track newly published medical literature across targeted specialty journals.