… In this paper, the main focus is to predict the liver disease based on a software engineering
approach using classification and feature selection technique. The implementation of …

… disease early on. This research proposed intelligent model to predict liver disease using …
machine learning (ANN) approach. The proposed model shows better performance in terms …

… Prediction of Liver Malady Using Advanced Classification … In this paper, the author used
SVM to predict liver disease using … of data science, such as scientific computing, computational …

… using data mining techniques. In this research paper, they created a classifications model for
diagnosis and to forecast liver problems using 5 data … on machine learning approaches. In …

… are using liver patient dataset to predict whether the patient is having liver disease or not. …
we can use the bootstrap sampling approach to select random samples of the same size from …

… is to develop prediction models for Chronic Hepatitis C (CHC)-related HCC using machine
… -consuming but still accurate and effective early prediction of fibrosis and liver cancer [13,14]. …

… many new insights into better ways we care for our patients with chronic liver disease, including
non-alcoholic fatty liver disease and liver fibrosis. There are multiple ways to apply the AI …

… AI refers to computational approaches to data analysis in which computer programmes
are … Throughout this article, we will use AI as a broad term that includes classical machine …

… [45] presented an HMM-based framework for predicting … hybrid prognosis approach for
age-dependent health prediction in terms … engineering, data mining, soft computing, management …

… of liver cancer. Machine learning methods were utilised in the prediction of liver cancer, …
The BUPA liver disorder training set (70 percent) and testing set (30 percent) were chosen, …