AIMC Topic: Students, Medical

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Understanding how medical students learn in the era of artificial intelligence: a mixed methods study.

BMC medical education
BACKGROUND: As medical education evolves, current teaching practices often remain misaligned with how today's digitally native students prefer to learn. While the use of digital tools is widespread, there is limited clarity on students' learning beha...

Academic misconduct and artificial intelligence use by medical students, interns and PhD students in Ukraine: a cross-sectional study.

BMC medical education
BACKGROUND: The issues regarding the use of artificial intelligence (AI) and academic integrity are important contemporary topics. There are no clear regulations governing the use of AI in academic institutions in Ukraine. This study aimed to explore...

Generative AI in medical education: feasibility and educational value of LLM-generated clinical cases with MCQs.

BMC medical education
OBJECTIVE: To evaluate the feasibility and educational value of employing large language models (LLMs) to generate clinical case scenario with multiple-choice questions (MCQs) for undergraduate medical education.

Application of AI Communication Training Tools in Medical Undergraduate Education: Mixed Methods Feasibility Study Within a Primary Care Context.

JMIR medical education
BACKGROUND: Effective communication is fundamental to high-quality health care delivery, influencing patient satisfaction, adherence to treatment plans, and clinical outcomes. However, communication skills training for medical undergraduates often fa...

AI's Accuracy in Extracting Learning Experiences From Clinical Practice Logs: Observational Study.

JMIR medical education
BACKGROUND: Improving the quality of education in clinical settings requires an understanding of learners' experiences and learning processes. However, this is a significant burden on learners and educators. If learners' learning records could be aut...

Revisiting medical oaths: how student-driven ethical codes reflect changing values.

Journal of medical ethics
BACKGROUND: Medical oaths and ethical codes play a crucial role in guiding physicians through their professional responsibilities. This study extends prior research on ethical codes created by students at the Medical School for International Health (...

Perception of Medical Undergraduates on Artificial Intelligence in Medical Education: Qualitative Exploration.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) has revolutionized medical education by delivering tools that enhance and optimize learning. However, there is limited research on the medical students' perceptions regarding the effectiveness of AI as a learn...

Knowledge and Perceptions of AI Among Medical Students in Morocco: Cross-Sectional Study.

JMIR formative research
BACKGROUND: Artificial intelligence (AI) is rapidly transforming medical practice by enhancing diagnostic accuracy, streamlining workflows, and supporting clinical decision-making. However, the integration of AI into health care largely depends on th...

Use of a Large Language Model as a Dermatology Case Narrator: Exploring the Dynamics of a Chatbot as an Educational Tool in Dermatology.

JMIR dermatology
A comparison of dermatological cases generated by artificial intelligence (AI) versus those created without AI by medical students revealed that AI-created cases were characterized by detailed case descriptions, analysis of medical history, and clini...

Development of a Clinical Clerkship Mentor Using Generative AI and Evaluation of Its Effectiveness in a Medical Student Trial Compared to Student Mentors: 2-Part Comparative Study.

JMIR medical education
BACKGROUND: At the beginning of their clinical clerkships (CCs), medical students face multiple challenges related to acquiring clinical and communication skills, building professional relationships, and managing psychological stress. While mentoring...