GenAI Assisting Medical Training
Project Overview
The document explores the integration of generative AI in education, particularly in medical training, highlighting its potential to enhance skill acquisition and improve learning outcomes. In the context of procedures like venipuncture and cannulation, generative AI tools provide real-time feedback to nursing students, which not only alleviates the workload of educators but also personalizes the learning experience by offering tailored insights based on individual performance. By utilizing data from training videos, sensor recordings, and advanced language models, these AI applications facilitate immediate feedback during training sessions, thereby fostering a more effective and interactive educational environment. The findings indicate that such innovative use of generative AI can significantly enhance the skill development process in medical education, preparing students more effectively for clinical practice. Overall, the document underscores the transformative impact of generative AI in educational settings, emphasizing its role in enriching the teaching and learning dynamics.
Key Applications
Real-time feedback system for medical procedures using generative AI
Context: Nursing training programs for students learning venipuncture and cannulation
Implementation: Integration of training videos, sensor data, and a large language model to provide live feedback during training sessions.
Outcomes: Improved skill acquisition for students, reduced workload for instructors, and enhanced learning experience.
Challenges: Complexity of procedures, variability in expert guidance, and the need for precise real-time feedback.
Implementation Barriers
Technical
The challenge of accurately providing real-time feedback during complex medical procedures.
Proposed Solutions: Developing methods for video classification and feedback generation through large language models.
Resource
Limited availability of instructors to provide one-on-one training in large classes.
Proposed Solutions: Using AI to supplement instructor feedback and improve student learning outcomes.
Project Team
Stefan Fritsch
Researcher
Matthias Tschoepe
Researcher
Vitor Fortes Rey
Researcher
Lars Krupp
Researcher
Agnes Gruenerbl
Researcher
Eloise Monger
Researcher
Sarah Travenna
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Stefan Fritsch, Matthias Tschoepe, Vitor Fortes Rey, Lars Krupp, Agnes Gruenerbl, Eloise Monger, Sarah Travenna
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai