Applied artificial intelligence in healthcare research with bibliometric approach

Artificial intelligence (AI) in healthcare is becoming increasingly important, given its potential to optimize healthcare resources, such as generating and analyzing healthcare data, facilitating better patient experiences, increasing healthcare professional satisfaction, reducing per capita costs, and increasing population health. Most research focuses on the potential benefits and barriers of implementing AI in healthcare. At the same time, only a few describe rational research opportunities and trends for developing Applied Artificial Intelligence in Healthcare research. In this study, a graphical mapping of scientific publications and research trends in the Applied Artificial Intelligence in the Healthcare sector worldwide was conducted using biometric analysis. The Scopus database was used to collect information and conduct online analysis using the Scopus website. A demonstration of bibliometric network mapping was conducted using VOSViewer. The selection of articles starts by searching based on the desired keywords and year restrictions. Then the database was exported as RIS and CSV format files. Based on the search results from the Scopus database for the last five years, researchers obtained 492 scientific publications published between 2012 and 2021. We also use VOSViewer to map the network. According to the database, researchers in United States had the most published papers indexed by Scopus among the most prolific authors (N=98), with the India coming second (N=72) and the China third (N=48). This study recommends combining the research subjects of Applied Artificial Intelligence in Healthcare: Internet, Covid, Artificial Intelligence, Dataset, abbreviated with the ICAD research theme.