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Related Experiment Video

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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

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Published on: December 6, 2024

Medical education empowered by generative artificial intelligence large language models.

Tanisha Jowsey¹, Jessica Stokes-Parish¹, Rachelle Singleton²

¹Faculty of Health Sciences and Medicine, Bond University, Robina, Australia.

Trends in Molecular Medicine

|September 17, 2023

Summary

Generative artificial intelligence (GAI) large language models (LLMs) offer new teaching tools for medical and health science educators. Integrating these AI technologies can enhance students

Keywords:

artificial intelligence education large language model machine learning

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Area of Science:

Medical Education
Artificial Intelligence in Healthcare
Digital Learning Technologies

Background:

Generative artificial intelligence (GAI) and large language models (LLMs) are rapidly evolving applications.
The increasing prevalence of GAI-LLMs necessitates their exploration within academic settings.
Medical and health science (M&HS) education faces the challenge of adapting to new digital tools.

Purpose of the Study:

To offer practical strategies for integrating GAI-LLMs into M&HS learning and teaching.
To guide educators on leveraging GAI-LLMs to improve student digital capabilities.
To explore the potential of AI in modernizing health science pedagogy.

Main Methods:

Review of current GAI-LLM capabilities relevant to education.
Development of pedagogical integration frameworks for M&HS.
Identification of best practices for ethical and effective AI use in classrooms.

Main Results:

Specific, actionable strategies for incorporating GAI-LLMs into M&HS curricula.
Examples of how GAI-LLMs can support diverse learning activities.
Guidance on fostering critical evaluation of AI-generated content among students.

Conclusions:

GAI-LLMs present significant opportunities for enhancing M&HS education.
Strategic integration of these tools can effectively boost students' digital literacy.
Educators play a crucial role in guiding the responsible adoption of AI in health sciences.