AIMC Topic: Education, Medical, Undergraduate

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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'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...

Is AI the future of evaluation in medical education?? AI vs. human evaluation in objective structured clinical examination.

BMC medical education
BACKGROUND: Objective Structured Clinical Examinations (OSCEs) are widely used in medical education to assess students' clinical and professional skills. Recent advancements in artificial intelligence (AI) offer opportunities to complement human eval...

Readiness towards artificial intelligence among medical and dental undergraduate students in Peshawar, Pakistan: a cross-sectional survey.

BMC medical education
INTRODUCTION: Artificial intelligence is a transformative tool for improving healthcare delivery and diagnostic accuracy in the medical and dental fields. This study aims to assess the readiness of future healthcare workers for artificial intelligenc...

Integrating AI in medical education: a comprehensive study of medical students' attitudes, concerns, and behavioral intentions.

BMC medical education
BACKGROUND: To analyze medical students' perceptions, trust, and attitudes toward artificial intelligence (AI) in medical education, and explore their willingness to integrate AI in learning and teaching practices.

Exploring the influence of artificial intelligence integration on personalized learning: a cross-sectional study of undergraduate medical students in the United Kingdom.

BMC medical education
BACKGROUND: With the integration of Artificial Intelligence (AI) into educational systems, its potential to revolutionize learning, particularly in content personalization and assessment support, is significant. Personalized learning, supported by AI...

Leveraging Datathons to Teach AI in Undergraduate Medical Education: Case Study.

JMIR medical education
BACKGROUND: As artificial intelligence and machine learning become increasingly influential in clinical practice, it is critical for future physicians to understand how such novel technologies will impact the delivery of patient care.

Mapping the use of artificial intelligence in medical education: a scoping review.

BMC medical education
INTRODUCTION: The integration of artificial intelligence (AI) in healthcare has transformed clinical practices and medical education, with technologies like diagnostic algorithms and clinical decision support increasingly incorporated into curricula....

GPT-4 generated answer rationales to multiple choice assessment questions in undergraduate medical education.

BMC medical education
BACKGROUND: Pre-clerkship medical students benefit from practice questions that provide rationales for answer choices. Creating these rationales is a time-intensive endeavor. Therefore, not all practice multiple choice questions (MCQ) have correspond...