A Bibliometric Analysis of Artificial Intelligence Revolutions in Health-related SDGs
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...
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| Format: | Article |
| Language: | English |
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Tehran University of Medical Sciences
2023-12-01
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| Series: | Health Technology Assessment in Action |
| Subjects: | |
| Online Access: | https://htainaction.tums.ac.ir/index.php/hta/article/view/201 |
| _version_ | 1827385688187731968 |
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| author | Maryam Ramezani Amirhossein Takian Ahad Bakhtiari Hamid R. Rabiee Saharnaz Sazgarnejad |
| author_facet | Maryam Ramezani Amirhossein Takian Ahad Bakhtiari Hamid R. Rabiee Saharnaz Sazgarnejad |
| author_sort | Maryam Ramezani |
| collection | DOAJ |
| description |
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.
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| first_indexed | 2024-03-08T15:31:13Z |
| format | Article |
| id | doaj.art-fbd7604d5e3645deb160d5ec47401bed |
| institution | Directory Open Access Journal |
| issn | 2645-3835 |
| language | English |
| last_indexed | 2024-03-08T15:31:13Z |
| publishDate | 2023-12-01 |
| publisher | Tehran University of Medical Sciences |
| record_format | Article |
| series | Health Technology Assessment in Action |
| spelling | doaj.art-fbd7604d5e3645deb160d5ec47401bed2024-01-10T06:03:23ZengTehran University of Medical SciencesHealth Technology Assessment in Action2645-38352023-12-017410.18502/htaa.v7i4.14654A Bibliometric Analysis of Artificial Intelligence Revolutions in Health-related SDGsMaryam Ramezani0Amirhossein Takian1Ahad Bakhtiari2Hamid R. Rabiee3Saharnaz Sazgarnejad4Department of Health Management, Policy and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, IranDepartment of Global Health and Public Policy, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. (Corresponding author: takian@tums.ac.ir)3. Health Equity Research Centre (HERC), Tehran University of Medical Sciences, Tehran, Iran.Department of Computer Engineering, Sharif University of Technology, Tehran, Iran.School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. 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. https://htainaction.tums.ac.ir/index.php/hta/article/view/201Artificial intelligence, Revolutions, Health, SDGs |
| spellingShingle | Maryam Ramezani Amirhossein Takian Ahad Bakhtiari Hamid R. Rabiee Saharnaz Sazgarnejad A Bibliometric Analysis of Artificial Intelligence Revolutions in Health-related SDGs Health Technology Assessment in Action Artificial intelligence, Revolutions, Health, SDGs |
| title | A Bibliometric Analysis of Artificial Intelligence Revolutions in Health-related SDGs |
| title_full | A Bibliometric Analysis of Artificial Intelligence Revolutions in Health-related SDGs |
| title_fullStr | A Bibliometric Analysis of Artificial Intelligence Revolutions in Health-related SDGs |
| title_full_unstemmed | A Bibliometric Analysis of Artificial Intelligence Revolutions in Health-related SDGs |
| title_short | A Bibliometric Analysis of Artificial Intelligence Revolutions in Health-related SDGs |
| title_sort | bibliometric analysis of artificial intelligence revolutions in health related sdgs |
| topic | Artificial intelligence, Revolutions, Health, SDGs |
| url | https://htainaction.tums.ac.ir/index.php/hta/article/view/201 |
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