• Sadhana Shah
• Anurag Kumar
• Gagan Deep Singh

Diagnosis of liver disease at a preliminary stage is important for better treatment. It is a very challenging task for medical researchers to predict the disease in the early stages owing to subtle symptoms. Often the symptoms become apparent when it is too late. To overcome this issue, this project aims to improve liver disease diagnosis using machine learning approaches. The main objective of this research is to use classification algorithms to identify the liver patients from healthy individuals. This project also aims to compare the classification algorithms based on their performance factors. To serve the medicinal community for the diagnosis of liver disease among patients, a graphical user interface will be developed using python. In this study, we developed and compared the neural network classification models to predict liver disease accurately. However, the neural network model showed higher performance.

Machine Learning, Liver Patients, Classification Algorithm, Neural Network

"Prediction and Classification of Liver Disease Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.36-39, June 2019, Available :http://www.jetir.org/papers/JETIR1908007.pdf

"Prediction and Classification of Liver Disease Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp36-39, June 2019, Available at : http://www.jetir.org/papers/JETIR1908007.pdf