AIMC Topic: Students, Medical

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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...

Assessing medical students' readiness for artificial intelligence after pre-clinical training.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is becoming increasingly relevant in healthcare, necessitating healthcare professionals' proficiency in its use. Medical students and practitioners require fundamental understanding and skills development to m...

Assessing ChatGPT adoption in Jordanian medical education: a UTAUT model approach.

BMC medical education
BACKGROUND: ChatGPT has shown significant promise in transforming medical education by streamlining research and improving teaching methods. However, its adoption in Middle Eastern medical education has remained underexplored. This study investigated...

Auxiliary Teaching and Student Evaluation Methods Based on Facial Expression Recognition in Medical Education.

JMIR human factors
Traditional medical education encounters several challenges. The introduction of advanced facial expression recognition technology offers a new approach to address these issues. The aim of the study is to propose a medical education-assisted teaching...

Assessing ChatGPT's Capability as a New Age Standardized Patient: Qualitative Study.

JMIR medical education
BACKGROUND: Standardized patients (SPs) have been crucial in medical education, offering realistic patient interactions to students. Despite their benefits, SP training is resource-intensive and access can be limited. Advances in artificial intellige...

Examining the empathy levels of medical students using CHAID analysis.

BMC medical education
BACKGROUND: Empathy is a key factor in the medical field as it strengthens doctor-patient relationships, enhances communication, and leads to improved patient outcomes. This study aims to investigate the empathy levels of medical students, providing ...