Articles / Reviews / Guidelines
Published July 9, 2024 | Clinics in Medical Education
Issue 1 | Volume 1 | July 2024
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Artificial Intelligence for Anesthesiology Board-Style Examination Questions: Role of Large Language Models
New artificial intelligence tools have been developed that have implications for medical usage. Large language models (LLMs), such as ChatGPT developed by OpenAI, have not been explored in the context of anesthesiology education. Understanding the reliability of various publicly available LLMs for medical specialties could offer insight into their understanding of the physiology, pharmacology, and practical applications of anesthesiology. An exploratory prospective review was conducted using 3 commercially available LLMs–OpenAI’s ChatGPT GPT-3.5 version (GPT-3.5), OpenAI’s ChatGPT GPT-4 (GPT-4), and Google’s Bard–on questions from a widely used anesthesia board examination review book.
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AI and Medical Education — A 21st-Century Pandora’s Box
To create a customized Large Language Model (LLM) for anesthesia education, it is essential to compile a comprehensive and tailored dataset. This involves sourcing information from authoritative anesthesia textbooks, up-to-date literature, peer-reviewed anesthesia journals, and relevant guidelines from related fields like cardiology. By incorporating these specialized resources, we can develop focused lectures, problem-based learning discussions, and rotation-specific teaching materials. This approach ensures that educational content is not only comprehensive but also highly relevant to the specific needs and challenges of anesthesia practice.
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2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines
To address the evolving role of biomarkers and structural changes for recognition of patients who are at risk of developing HF, potential candidates for targeted treatment strategies for the prevention of HF, and to enhance the understanding and adoption of these classifications, the writing committee proposed the terminologies Stage A (at risk for HF), Stage B (Pre-HF), Stage C (Symptomatic HF) and Stage D (advanced HF).