The Advent of Generative Language Models in Medical Education
Mount Sinai Health System · The University of Texas MD Anderson Cancer Center · +3 more institutions
Abstract
Artificial intelligence (AI) and generative language models (GLMs) present significant opportunities for enhancing medical education, including the provision of realistic simulations, digital patients, personalized feedback, evaluation methods, and the elimination of language barriers. These advanced technologies can facilitate immersive learning environments and enhance medical students' educational outcomes. However, ensuring content quality, addressing biases, and managing ethical and legal concerns present obstacles. To mitigate these challenges, it is necessary to evaluate the accuracy and relevance of AI-generated content, address potential biases, and develop guidelines and policies governing the use of…
Citation impact
- FWCI
- 7.18
- Percentile
- 100%
- References
- 12
Authors
5- MKMert KarabacakCorresponding
Mount Sinai Health System
- BBBurak Berksu Ozkara
The University of Texas MD Anderson Cancer Center
- KMKonstantinos Margetis
Mount Sinai Health System
- MWMax Wintermark
The University of Texas MD Anderson Cancer Center
- SBSotirios Bisdas
University College London Hospitals NHS Foundation Trust, The University of Texas MD Anderson Cancer Center, National Hospital for Neurology and Neurosurgery, University College London
Topics & keywords
- Credibility
- Relevance (law)
- Computer science
- Quality (philosophy)
- Knowledge management
- Medical education
- Medicine
- Political science