Generative Adversarial Networks in Healthcare Sector

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R. Jain
M. Pant
N.K. Tripathi

Abstract

Generative Adversarial Networks widely known as GANs, are deep learning models that has gained a lot of popularity in the last few years due to their promising nature. One of their major applications can be found in the healthcare sector for various purposes like image reconstruction, image enhancement, image segmentation, image processing, image analysis etc. The objective of this paper is to bring forward some of the recent research on the application of GANs in the health care domain during 2017 – 2022. A total of 168 papers were screened out of which 77 relevant to the present study were finalized for this study. Bibliometric analysis was also performed on these documents, to obtain an overall picture of Generative Adversarial Networks (GANs) in the healthcare domain. This analysis is expected to help the future researcher and developers in targeting the areas of the healthcare sector which are likely to grow in the coming future using GANs algorithms.

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How to Cite
Jain, R., Pant, M., & Tripathi, N. (2024). Generative Adversarial Networks in Healthcare Sector. International Journal of Geoinformatics, 20(6), 26–42. https://doi.org/10.52939/ijg.v20i6.3331
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