Mapping the Impact of Artificial Intelligence on Trauma Research via Scientometric Analysis

Abstract

Background: Medical progress has often been hindered by the inherent limitations of human ability to process large volumes of data. The application of Artificial Intelligence (AI) can help overcome this constraint, particularly in the field of trauma. Purpose and Objectives: This study aims to analyze the application of artificial intelligence in the field of trauma through visualization tools, predict future research hotspots, and explore the potential applications of related technologies in the field of trauma, especially traumatic brain injury (TBI). Materials and Methods: Based on the Web of Science database, this study utilized visualization tools such as CiteSpace, VOSviewer, and SciMAT to create a knowledge map of AI applications in trauma from 1979 to 2022. Results: The analysis indicates that traumatic brain injury (TBI) will be a focal point for future research on the use of AI in trauma. Additionally, terms related to machine learning, including Artificial Neural Network and Convolutional Neural Network, are expected to be extensively employed in trauma detection and prediction. These targeted algorithms hold significant potential for groundbreaking applications in TBI. Conclusion: Artificial intelligence, especially machine learning techniques, will play a crucial role in the research and application of trauma, particularly TBI. In the future, these technologies are expected to provide new methods and perspectives for TBI detection, prediction, and treatment.

Keywords

• citespace
• knowledge mapping
• machine learning
• scimat
• traumatic brain injury
• vosviewer