Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review
- Journal
- Electronics
In The Last Decade
doi.org/10.3390/electronics12051102 →Countries where authors are citing Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review
This map shows the geographic impact of Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review more than expected).
Fields of papers citing Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review
This network shows the impact of Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review.
About Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review
This paper, published in 2023, received 92 indexed citations . Written by Vasile-Daniel Păvăloaia and Sabina-Cristiana Necula covering the research area of Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Information Systems. It is primarily cited by scholars working on Artificial Intelligence (25 citations), Health Informatics (15 citations) and Information Systems (12 citations). Published in Electronics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/10.3390/electronics12051102.