AIMC Topic: Education, Medical

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Ten tips to harnessing generative AI for high-quality MCQS in medical education assessment.

Medical education online
Generating high quality MCQs is time consuming and expensive. Many strategies are applied to produce high quality items including sharing of item banks, training of item writers and automatic item generation (AIG). Generative AI, when used with preci...

Large language models in medical education: a comparative cross-platform evaluation in answering histological questions.

Medical education online
Large language models (LLMs) have shown promising capabilities across medical disciplines, yet their performance in basic medical sciences remains incompletely characterized. Medical histology, requiring factual knowledge and interpretative skills, p...

Feasibility study of using GPT for history-taking training in medical education: a randomized clinical trial.

BMC medical education
BACKGROUNDS: Traditional methods of teaching history-taking in medical education are limited by scalability and resource intensity. This study aims to assess the effectiveness of simulated patient interactions based on a custom-designed Generative Pr...

Artificial Intelligence in Medical Education.

Anesthesiology clinics
Artificial intelligence (AI) provides tremendous opportunities for growth in medical education. With advances in technology, AI systems can now augment a variety of workflows critical to education. This article reviews the scope and some key use case...

Medical simulation: an essential tool for training, diagnosis, and treatment in the 21st century.

BMC medical education
BACKGROUND: Medical simulation is a global trend that improves disease interpretation, diagnostic skills, and clinical abilities, transforming them into skills for the practitioner. Simulator classes should be part of continuing medical education, ge...

A comparative analysis of DeepSeek R1, DeepSeek-R1-Lite, OpenAi o1 Pro, and Grok 3 performance on ophthalmology board-style questions.

Scientific reports
The ability of large language models (LLMs) to accurately answer medical board-style questions reflects their potential to benefit medical education and real-time clinical decision-making. With the recent advance to reasoning models, the latest LLMs ...

Preparing Tomorrow's Physicians: The Case for Machine Learning in Medical Education.

Journal of medical systems
Machine learning should be integrated into medical curricula to prepare physicians-in-training for 21st-century practice conditions. This comment proposes practical implementation strategies that build upon existing educational frameworks by drawing ...

Macy Foundation Innovation Report Part II: From Hype to Reality: Innovators' Visions for Navigating AI Integration Challenges in Medical Education.

Academic medicine : journal of the Association of American Medical Colleges
PURPOSE: Artificial intelligence (AI) promises to significantly impact medical education, yet its implementation raises important questions about educational effectiveness, ethical use, and equity. In the second part of a 2-part innovation report, wh...

Macy Foundation Innovation Report Part I: Current Landscape of Artificial Intelligence in Medical Education.

Academic medicine : journal of the Association of American Medical Colleges
The rapid emergence of artificial intelligence (AI), including generative large language models, offers transformative opportunities in medical education. This proliferation has generated numerous speculative discussions about AI's promise but has be...

Learning to care, caring to learn: the evolving nature of medical education.

The New Zealand medical journal
As Otago Medical School marks its 150th anniversary, this paper reflects on what it means to train doctors for both today and the decades ahead. It traces the school's evolution from its nineteenth-century foundations through key innovations in curri...