Author:
Zhu Kunshu,Shen Zefang,Wang Min,Jiang Lufang,Zhang Ye,Yang Tiantong,Zhang Haidong,Zhang Mengzhou
Abstract
Abstract
Artificial intelligence (AI)–assisted medical imaging technology is a new research area of great interest that has developed rapidly over the last decade. However, there has been no bibliometric analysis of published studies in this field. The present review focuses on AI-related studies on computed tomography imaging in the Web of Science database and uses CiteSpace and VOSviewer to generate a knowledge map and conduct the basic information analysis, co-word analysis, and co-citation analysis. A total of 7265 documents were included and the number of documents published had an overall upward trend. Scholars from the United States and China have made outstanding achievements, and there is a general lack of extensive cooperation in this field. In recent years, the research areas of great interest and difficulty have been the optimization and upgrading of algorithms, and the application of theoretical models to practical clinical applications. This review will help researchers understand the developments, research areas of great interest, and research frontiers in this field and provide reference and guidance for future studies.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Reference47 articles.
1. Artificial intelligence and machine learning in radiology: opportunities, challenges, pitfalls, and criteria for success;J Am Coll Radiol,2018
2. Machine learning in medicine;Circulation,2015
3. Artificial intelligence in surgery: promises and perils;Ann Surg,2018
4. Overview of deep learning in medical imaging;Radiol Phys Technol,2017
5. International evaluation of an AI system for breast cancer screening;Nature,2020