TIM-6074

Alhashmi, S. M., Hashem, I. A. T., & Al-Qudah, I. (2024). Artificial intelligence applications in healthcare: A bibliometric and topic model-based analysis. Intelligent Systems with Applications, 21, 200299. https://www.sciencedirect.com/science/article/pii/S2667305323001242
This paper conducts a bibliometric and topic model analysis of AI applications in healthcare to reveal research trends and hot topics.

Doğan, E., & Şahin, F. (2024). Advances in artificial intelligence in education: Leading contributors, current hot topics, and emerging trends. Participatory Educational Research, 11(Prof. Dr. H. Ferhan Odabaşı Gift Issue), 95–113. https://dergipark.org.tr/en/pub/per/issue/84122/1559629
This study uses bibliometric analysis to explore the landscape of AI research in education, identifying key contributors, current hot topics, and emphasizing future research on ethical frameworks and guidelines.

Manduva, V. C. (2024). Current State and Future Directions for AI Research in the Corporate World. The Metascience, 2(4), 70–83. http://yuktabpublisher.com/index.php/TMS/article/view/92
This study surveys recent work on AI in corporate settings, presenting key developmental trends, problems, and a research agenda, including discussions on ethical principles and the law.

Raman, R., Pattnaik, D., Lathabai, H. H., Kumar, C., Govindan, K., & Nedungadi, P. (2024). Green and sustainable AI research An integrated thematic and topic modeling analysis. Journal of Big Data, 11(1), 55. https://doi.org/10.1186/s40537-024-00920-x
This systematic review of reviews uses scientometrics and BERTopic modeling to investigate AI research dynamics, revealing transformative impacts across various domains, key research themes, and highlighting ethical considerations and bias mitigation as critical elements.

Raman, R., Pattnaik, D., Hughes, L., & Nedungadi, P. (2024). Unveiling the dynamics of AI applications: A review of reviews using scientometrics and BERTopic modeling. Journal of Innovation & Knowledge, 9(3), 100517. https://www.sciencedirect.com/science/article/pii/S2444569X24000568
This investigation analyzes Green and Sustainable AI literature through thematic and topic modeling, identifying major themes and emerging topics while advocating for integrating ethical and environmental considerations.

Sai, S., Gaur, A., Sai, R., Chamola, V., Guizani, M., & Rodrigues, J. J. P. C. (2024). Generative AI for transformative healthcare: A comprehensive study of emerging models, applications, case studies, and limitations. IEEE Access, 12, 31078–31106. https://doi.org/10.1109/ACCESS.2024.3367715
This paper provides a comprehensive study of Generative AI in healthcare, exploring emerging models, applications, real-world scenarios, and limitations, including detailed discussions on ethical and legal considerations, data privacy, and bias.