Sentiment analysis has come long way since it was introduced as a natural language
processing task nearly 20 years ago. Sentiment analysis aims to extract the underlying …

This review presents a comprehensive exploration of hybrid and ensemble deep learning
models within Natural Language Processing (NLP), shedding light on their transformative …

Sentiment analysis (SA) is a widely used contextual mining technique for extracting useful
and subjective information from text-based data. It applies on Natural Language Processing …

Sentiment analysis on public opinion expressed in social networks, such as Twitter or
Facebook, has been developed into a wide range of applications, but there are still many …

Alzheimer's disease (AD) may cause damage to the memory cells permanently, which
results in the form of dementia. The diagnosis of Alzheimer's disease at an early stage is a …

Aspect-based sentiment classification (ABSC) aims to predict sentiment polarities of different
aspects within sentences or documents. Many previous studies have been conducted to …

Background Discharge medical notes written by physicians contain important information
about the health condition of patients. Many deep learning algorithms have been …

This paper presents, TextConvoNet, a novel Convolutional Neural Network (CNN) based
architecture for binary and multi-class text classification problems. Most of the existing CNN …

A vast amount of data is generated every second for microblogs, content sharing via social
media sites, and social networking. Twitter is an essential popular microblog where people …

Featured Application Combining of multi-features extracted manually and convolutional
neural network classifier for automatic heart sounds classification. Abstract Heart sounds …