Results 191 to 200 of about 18,589 (259)

Impacts of body donor non‐anonymization on students' educational and humanistic development: A systematic review

open access: yesAnatomical Sciences Education, EarlyView.
Abstract A recent trend in healthcare education has been the increasing emphasis on the development of humanism and empathy in students. Within anatomy education, some institutions have implemented curricular innovations such as donor non‐anonymization to facilitate this development.
Rodrigo Muscogliati   +5 more
wiley   +1 more source

Online anatomical images are an effective resource to improve knowledge acquisition and practical exam performance in gross anatomy

open access: yesAnatomical Sciences Education, EarlyView.
The use of cadaveric images in visceral anatomy is associated with improved knowledge acquisition, higher motivation and satisfaction. Besides, the use of anatomical images significantly improved students' practical exam performance in the dissection room.
Amparo Gimeno   +4 more
wiley   +1 more source

Is artificial intelligence getting better at anatomy? A two‐year review of ChatGPT's free public versions

open access: yesAnatomical Sciences Education, EarlyView.
Abstract Artificial intelligence and large language models have significantly influenced medical education by enhancing learning experiences. While previous studies have assessed ChatGPT's performance on anatomy‐related questions, a notable gap remains in understanding its accuracy over time. This longitudinal study evaluated the progression of ChatGPT'
Bahattin Paslı, Ceren Günenç Beşer
wiley   +1 more source

Performance of multimodal large language models on image‐based surgical anatomy, anatomical pathology, and radiology questions

open access: yesAnatomical Sciences Education, EarlyView.
Abstract Multimodal large language models (LLMs) are now deeply integrated into medical education and widely used by medical students, yet it remains unclear whether current models possess the accuracy and reliability needed to support image‐based learning.
Ming Lu, Josiah Cheng, Vinod Gopalan
wiley   +1 more source

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