Bibliometric Analysis of Artificial Intelligence Revolutions in Healthrelated Sustainable Development Goals

  • Maryam Ramezani Department of Health Management, Policy and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  • Amirhossein Takian Department of Health Management, Policy and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  • Ahad Bakhtiari Health Equity Research Centre (HERC), Tehran University of Medical Sciences, Tehran, Iran
  • Hamid R. Rabiee Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
  • Saharnaz Sazgarnejad Department of Global Health and Public Policy, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
Keywords: Artificial Intelligence; Revolutions; Health; Sustainable Development Goals

Abstract

Background: In line with the advancement of Artificial Intelligence (AI), innovative solutions have been designed to improve healthrelated Sustainable Development Goals (SDGs). Accordingly, there is an increasing trend in the realm of AI and SDG research areas.

Objectives: This study aimed to analyze the trends and patterns of AI research in health-related SDGs using bibliometric analysis.

Methods: The bibliometric approach facilitated the identification of key terms and countries from previous research. We used VOSviewer to map and analyze data obtained from three databases: Scopus, Web of Science, and PubMed.

Results: Our findings illustrated that research on health has been a popular area of study in recent years. In particular, we observed a significant increase in research on AI in health-related SDGs during 2015 - 2022.

Conclusions: This study provides insights into the trends and patterns of AI research in health-related SDGs using bibliometric analysis. The findings can guide future research by identifying key terms that require further investigation.

Published
2024-01-07
Section
Articles