Human-in-the-Loop AI in Medical Education and Board Preparation

New clinical trials, guideline updates, therapeutic approaches, and diagnostic technologies are continually reshaping how oncology clinicians learn and practice, far beyond traditional board-review methods. In this episode of Exploring AI in Oncology, Dr. Roupen Odabashian and Dr. Waqas Haque explore how human-guided AI can transform medical education, why clinician oversight is non-negotiable in content creation, and how oncology professionals can build practical AI literacy. Read the full accompanying article on Oncology Data Advisor: https://oncdata.com/reimagining-oncology-education-with-ai What You’ll Learn in This Episode: 🔹 From Fellowship to AI Development: How Dr. Odabashian transitioned from clinical training to independently learning Python, calculus, and multi-agent systems to bridge oncology and software engineering. 🔹 Building Adaptive Learning Platforms: Developing MeducationAI with question banks, flashcards, notes, visual materials, and podcasts to support diverse learning styles for trainees and attendings. 🔹 The "Human in the Loop" Imperative: Why physician review is essential when using AI tools for literature retrieval, question drafting, and determining board examination relevance. 🔹 Identifying AI Pitfalls & Limitations: Analyzing clinical scenarios where AI models fail without expert oversight, including defaulting to incorrect patient demographics or missing updated guideline changes. 🔹 Practical Pathways to AI Literacy: Defining three levels of clinician engagement—from basic AI literacy and workflow development ("plumbing") to technical model creation. 🔹 AI as a Clinical Capability Multiplier: Why AI resembles PCR testing and DNA sequencing as a powerful tool that expands clinical potential rather than replacing the physician-patient relationship.