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This study aims to examine the temporal evolution and changes of research interests and trends in the educational augmented reality (AR) literature. To this end, 3718 articles published in the 2003–2022 period and indexed in the Scopus database were analyzed through machine learning-based semantic topic modeling and descriptive analysis. The findings indicate a notable upswing in studies on educational AR, particularly since 2015. The articles were categorized into eleven primary themes through topic modeling analysis. The three most prevalent topics in terms of volume are “Augmented Reality in Education and Cultural Heritage”, “Medical Education and Patient Care”, and “Enhancing Safety and Information in Food Consumption”. Observations across different times reveal that “Augmented Reality in Electrical and Electronic Systems” and “Gesture-Based Instruction and Maintenance” were studied in the initial periods. Since 2015, there has been a notable increase in applications falling under the “Serious Games” category. The least voluminous and slowest-evolving topics are identified as “Serious Games for Children with Autism Spectrum Disorder”, “Augmented Reality in Chemistry and Biology Laboratories”, and “Augmented Reality for Safe and Efficient Driving”. Considering the recent momentum gained by these topics, it is anticipated that they will become popular topics for future studies. This study represents a significant milestone as the first and most comprehensive research using machine learning in its field, not only explaining the current state of the field but also providing valuable information for future research efforts.
This study aims to examine the temporal evolution and changes of research interests and trends in the educational augmented reality (AR) literature. To this end, 3718 articles published in the 2003–2022 period and indexed in the Scopus database were analyzed through machine learning-based semantic topic modeling and descriptive analysis. The findings indicate a notable upswing in studies on educational AR, particularly since 2015. The articles were categorized into eleven primary themes through topic modeling analysis. The three most prevalent topics in terms of volume are “Augmented Reality in Education and Cultural Heritage”, “Medical Education and Patient Care”, and “Enhancing Safety and Information in Food Consumption”. Observations across different times reveal that “Augmented Reality in Electrical and Electronic Systems” and “Gesture-Based Instruction and Maintenance” were studied in the initial periods. Since 2015, there has been a notable increase in applications falling under the “Serious Games” category. The least voluminous and slowest-evolving topics are identified as “Serious Games for Children with Autism Spectrum Disorder”, “Augmented Reality in Chemistry and Biology Laboratories”, and “Augmented Reality for Safe and Efficient Driving”. Considering the recent momentum gained by these topics, it is anticipated that they will become popular topics for future studies. This study represents a significant milestone as the first and most comprehensive research using machine learning in its field, not only explaining the current state of the field but also providing valuable information for future research efforts.
The integration of Advanced Artificial Intelligence (AI) and Augmented Reality (AR) in medical and surgical practices is revolutionizing healthcare by enhancing precision, efficiency, and patient outcomes. AI-driven tools, combined with AR visualization, enable real-time guidance during complex surgical procedures, improving accuracy and reducing complications. This research focuses on the development and application of AI algorithms for diagnostic imaging, robotic-assisted surgery, and personalized treatment planning. Coupled with AR, these technologies provide surgeons with enhanced visualization of anatomical structures, allowing for minimally invasive techniques and precise interventions. By leveraging AI's predictive analytics and AR's immersive capabilities, this study explores the potential to address challenges such as variability in surgical expertise and the demand for high-precision outcomes. The findings highlight the transformative impact of AI and AR on healthcare delivery, emphasizing their role in advancing patient care and operational efficiency.
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