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Comparison of the experience and perception of artificial intelligence among practicing doctors and medical students.

Wiadomosci lekarskie (Warsaw, Poland : 1960)
OBJECTIVE: Aim: To analyze and compare the experiences and perceptions of artificial intelligence (AI) among practicing doctors and medical students.

Food for thought: a qualitative assessment of medical trainee and faculty perceptions of nutrition education.

BMC medical education
BACKGROUND: The American Society of Clinical Nutrition recommends 37 to 44 h of undergraduate medical nutrition education. The Total Health Curriculum at Geisinger Commonwealth School of Medicine (GCSOM) contains 14 h of objective-based nutritional i...

Comment about 'Medical, dental, and nursing students' attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis'.

BMC medical education
We read with great interest the recently published article by Amiri et al., titled "Medical, Dental, and Nursing Students' Attitudes and Knowledge Toward Artificial Intelligence: A Systematic Review and Meta-Analysis." We would like to offer comments...

Artificial Intelligence (AI)-Based simulators versus simulated patients in undergraduate programs: A protocol for a randomized controlled trial.

BMC medical education
BACKGROUND: Healthcare simulation is critical for medical education, with traditional methods using simulated patients (SPs). Recent advances in artificial intelligence (AI) offer new possibilities with AI-based simulators, introducing limitless oppo...

Effect of feedback-integrated reflection, on deep learning of undergraduate medical students in a clinical setting.

BMC medical education
BACKGROUND: Reflection fosters self-regulated learning by enabling learners to critically evaluate their performance, identify gaps, and make plans to improve. Feedback, in turn, provides external insights that complement reflection, helping learners...

Awareness and Attitude Toward Artificial Intelligence Among Medical Students and Pathology Trainees: Survey Study.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) is set to shape the future of medical practice. The perspective and understanding of medical students are critical for guiding the development of educational curricula and training.

Application of ChatGPT-assisted problem-based learning teaching method in clinical medical education.

BMC medical education
INTRODUCTION: Artificial intelligence technology has a wide range of application prospects in the field of medical education. The aim of the study was to measure the effectiveness of ChatGPT-assisted problem-based learning (PBL) teaching for urology ...

Enhancing Medical Student Engagement Through Cinematic Clinical Narratives: Multimodal Generative AI-Based Mixed Methods Study.

JMIR medical education
BACKGROUND: Medical students often struggle to engage with and retain complex pharmacology topics during their preclinical education. Traditional teaching methods can lead to passive learning and poor long-term retention of critical concepts.

Widespread use of ChatGPT and other Artificial Intelligence tools among medical students in Uganda: A cross-sectional study.

PloS one
BACKGROUND: Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. Consequently, i...