AIMC Topic: Students, Medical

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Artificial intelligence assisted automated short answer question scoring tool shows high correlation with human examiner markings.

BMC medical education
BACKGROUND: Optimizing the skill of answering Short answer questions (SAQ) in medical undergraduates with personalized feedback is challenging. With the increasing number of students and staff shortages this task is becoming practically difficult. He...

Medical undergraduate students' awareness and perspectives on artificial intelligence: A developing nation's context.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is reshaping healthcare, yet its integration into medical education remains limited. This study assesses undergraduate healthcare students' knowledge and perceptions of AI, its applications, challenges, and th...

Predicting New York Heart Association (NYHA) heart failure classification from medical student notes following simulated patient encounters.

Scientific reports
Random forest models have demonstrated utility in the determination of New York Heart Association (NYHA) Heart Failure Classifications. This study aims to determine the prediction accuracy of a random forest model to derive NYHA Classification from m...

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...

Enhancing medical students' diagnostic accuracy of infectious keratitis with AI-generated images.

BMC medical education
BACKGROUND: Developing students' ability to accurately diagnose various types of keratitis is challenging. This study aims to compare the effectiveness of teaching methods-real cases, artificial intelligence (AI)-generated images, and real medical im...

Enhancing AI literacy in undergraduate pre-medical education through student associations: an educational intervention.

BMC medical education
BACKGROUND: The integration of artificial intelligence (AI) into healthcare is rapidly advancing, with profound implications for medical practice. However, a gap exists in formal AI education for pre-medical students. This study evaluates the effecti...

Explainable artificial intelligence for predicting medical students' performance in comprehensive assessments.

Scientific reports
Comprehensive medical assessments are critical for evaluating clinical proficiency in medical education; however, these administrations impose significant institutional burdens, financial costs, and psychological strain on students. While Artificial ...

Student perceptions of GenAI as a virtual tutor to support collaborative research training for health professionals.

BMC medical education
BACKGROUND: Research and evaluation skills are essential in healthcare education. Instructors frequently employ collaborative learning models to teach these competencies; however, delivering timely and personalized feedback to multiple groups can be ...

Large language models versus traditional textbooks: optimizing learning for plastic surgery case preparation.

BMC medical education
BACKGROUND: Large language models (LLMs), such as ChatGPT-4 and Gemini, represent a new frontier in surgical education by offering dynamic, interactive learning experiences. Despite their potential, concerns about the accuracy, depth of knowledge, an...

Assessment of Large Language Model Performance on Medical School Essay-Style Concept Appraisal Questions: Exploratory Study.

JMIR medical education
Bing Chat (subsequently renamed Microsoft Copilot)-a ChatGPT 4.0-based large language model-demonstrated comparable performance to medical students in answering essay-style concept appraisals, while assessors struggled to differentiate artificial int...