Transformers in healthcare: A survey

S Nerella, S Bandyopadhyay, J Zhang… - arXiv preprint arXiv …, 2023 - arxiv.org
With Artificial Intelligence (AI) increasingly permeating various aspects of society, including
healthcare, the adoption of the Transformers neural network architecture is rapidly changing …

A review on electronic health record text-mining for biomedical name entity recognition in healthcare domain

PN Ahmad, AM Shah, KY Lee - Healthcare, 2023 - mdpi.com
Biomedical-named entity recognition (bNER) is critical in biomedical informatics. It identifies
biomedical entities with special meanings, such as people, places, and organizations, as …

Sentiment analysis on Twitter data integrating TextBlob and deep learning models: The case of US airline industry

W Aljedaani, F Rustam, MW Mkaouer, A Ghallab… - Knowledge-Based …, 2022 - Elsevier
Twitter being among the popular social media platforms, provide peoples' opinions
regarding specific ideas, products, services, etc. The large amounts of shared data as tweets …

Counterfactual neural temporal point process for estimating causal influence of misinformation on social media

Y Zhang, D Cao, Y Liu - Advances in Neural Information …, 2022 - proceedings.neurips.cc
Recent years have witnessed the rise of misinformation campaigns that spread specific
narratives on social media to manipulate public opinions on different areas, such as politics …

E-Government 3.0: An AI model to use for enhanced local democracies

C Vrabie - Sustainability, 2023 - mdpi.com
While e-government (referring here to the first generation of e-government) was just the
simple manner of delivering public services via electronic means, e-gov 2.0 refers to the use …

Automatically detecting and understanding the perception of COVID-19 vaccination: a middle east case study

W Aljedaani, I Abuhaimed, F Rustam… - Social Network Analysis …, 2022 - Springer
Introduction The development of COVID-19 vaccines has been a great relief in many
countries that have been affected by the pandemic. As a result, many governments have …

COVID-19 vaccines related user's response categorization using machine learning techniques

A Shahzad, B Zafar, N Ali, U Jamil, AJ Alghadhban… - Computation, 2022 - mdpi.com
Respiratory viruses known as coronaviruses infect people and cause death. The multiple
crown-like spikes on the virus's surface give them the name “corona”. The pandemic has …

Sentiment analysis of Indonesian datasets based on a hybrid deep-learning strategy

CH Lin, U Nuha - Journal of Big Data, 2023 - Springer
Various attempts have been conducted to improve the performance of text-based sentiment
analysis. These significant attempts have focused on text representation and model …

[HTML][HTML] Applications of social media and digital technologies in COVID-19 vaccination: scoping review

S Zang, X Zhang, Y Xing, J Chen, L Lin… - Journal of medical Internet …, 2023 - jmir.org
Background Social media and digital technologies have played essential roles in
disseminating information and promoting vaccination during the COVID-19 pandemic. There …

A Review of Deep Learning Models for Twitter Sentiment Analysis: Challenges and Opportunities

L Chaudhary, N Girdhar, D Sharma… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Microblogging site Twitter (re-branded to X since July 2023) is one of the most influential
online social media websites, which offers a platform for the masses to communicate …