A Review of Generative Adversarial-Based Networks of Machine Learning/Artificial Intelligence in Healthcare
Anilkumar Suthar, Vedant Sandeep Joshi, Ramesh Prajapati
Abstract
Machine learning has been proven to be a game-changing technology in every domain since the late 20th century. There have been many advancements in healthcare not only for the diagnosis of disease but advanced in the prognosis of the diseases. Artificial intelligence/machine learning (AI/ML) has progressed a lot in the medical domain in just a couple of decades and played a very important role in exploring human data to understand human body behavior better than ever before, for predicting and classifying all kinds of medical images or videos. A recent and best-used application is detecting COVID-19 by just checking the chest x-ray in a very accurate manner that can be used without human presence and stop the spread of the virus resulting in fewer doctors getting affected. It is known as generative adversarial networks. Some of the types of GANs used for differentiate domains without human supervision and many such mutations of GANs are useful in the health sector. This is simply a quick review of various technologies that will become more in-depth as time goes on.