Analysis and Prediction of Liver Disease using Deep Learning - Akansha Moral, Dr. N. V. Kousik, Dr. E. Rajesh, Priyank Sirohi (International Journal of Advanced Science and Technology, 2020)
A Deep Learning (DL) algorithms plays a critical participation in predicting any kind of predictive disease in human. This paper focus on the prediction of liver disease using the DL algorithms. As known that the liver is most important port of human. So prior prediction or analysis if any kind of symptoms related to the disease may be useful in the diagnosis of the disease. This research investigate the disease of the basis of the past record of the disease. The trend analysis of the data under the deep learning algorithms is the core investigations of this paper. Data analysis enables in predicting liver ailment in the scientific discipline is an important assignment in the recent time. Data evaluation allows expect from a lot of information and allows medical institutions to predict the liver as well as various other diseases. The principal motive of this research paper is to demonstrate a certain deep learning algorithms that perform on data sets for prediction of their accuracy and Confusion Matrix (true false indicator).