In the healthcare domain, a transformative shift is envisioned towards Healthcare 5.0. It
expands the operational boundaries of Healthcare 4.0 and leverages patient-centric digital …

Learning algorithms can be less effective on datasets with an extensive feature space due to
the presence of irrelevant and redundant features. Feature selection is a technique that …

In stock market forecasting, the identification of critical features that affect the performance of
machine learning (ML) models is crucial to achieve accurate stock price predictions. Several …

Sentiment analysis (SA), also called Opinion Mining (OM) is the task of extracting and
analyzing people's opinions, sentiments, attitudes, perceptions, etc., toward different entities …

Artificial Intelligence (AI) is a fast-growing area of study that stretching its presence to many
business and research domains. Machine learning, deep learning, and natural language …

In the past decades, the rapid growth of computer and database technologies has led to the
rapid growth of large-scale datasets. On the other hand, data mining applications with high …

Consensus reaching process is a very powerful decision tool to eliminate the preference
conflict in group decision making. In general, the consensus is achieved by the decision …

Feature Selection, a critical data preprocessing step in machine learning, is an effective way
in removing irrelevant variables, thus reducing the dimensionality of input features …

The major objective of this paper is to introduce a novel multi-criteria decision making
method (MCDM) called Root Assessment Method (RAM) which is easy to understand …

As a river of great strategic significance in China, the ecological governance of the Yellow
River is an important issue. As a multi-attribute decision-making (MADM) problem …