AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Sentiment Analysis

Showing 1 to 10 of 103 articles

Clear Filters

Sentiment analysis of Indonesian tweets on COVID-19 and COVID-19 vaccinations.

F1000Research
BACKGROUND: Sentiments and opinions regarding COVID-19 and the COVID-19 vaccination on Indonesian-language Twitter are scarcely reported in one comprehensive study, and thus were aimed at our study. We also analyzed fake news and facts, and Twitter e...

Depression detection for twitter users using sentiment analysis in English and Arabic tweets.

Artificial intelligence in medicine
Since depression often results in suicidal thoughts and leaves a person severely disabled daily, there is an elevated risk of premature mortality due to mental problems caused by depression. Therefore, it's crucial to identify the patient's mental il...

Sentiment analysis using averaged weighted word vector features.

PloS one
People use the World Wide Web heavily to share their experiences with entities such as products, services or travel destinations. Texts that provide online feedback through reviews and comments are essential for consumer decisions. These comments cre...

Chinese text dual attention network for aspect-level sentiment classification.

PloS one
English text has a clear and compact subject structure, which makes it easy to find dependency relationships between words. However, Chinese text often conveys information using situational settings, which results in loose sentence structures, and ev...

Enhancing machine learning-based sentiment analysis through feature extraction techniques.

PloS one
A crucial part of sentiment classification is featuring extraction because it involves extracting valuable information from text data, which affects the model's performance. The goal of this paper is to help in selecting a suitable feature extraction...

A new word embedding model integrated with medical knowledge for deep learning-based sentiment classification.

Artificial intelligence in medicine
The development of intelligent systems that use social media data for decision-making processes in numerous domains such as politics, business, marketing, and finance, has been made possible by the popularity of social media platforms. However, the u...

A Comparison of ChatGPT and Fine-Tuned Open Pre-Trained Transformers (OPT) Against Widely Used Sentiment Analysis Tools: Sentiment Analysis of COVID-19 Survey Data.

JMIR mental health
BACKGROUND: Health care providers and health-related researchers face significant challenges when applying sentiment analysis tools to health-related free-text survey data. Most state-of-the-art applications were developed in domains such as social m...

How satisfied are patients with nursing care and why? A comprehensive study based on social media and opinion mining.

Informatics for health & social care
To assess the overall experience of a patient in a hospital, many factors must be analyzed; nonetheless, one of the key aspects is the performance of nurses as they closely interact with patients on many occasions. Nurses carry out many tasks that co...

Applying BERT and ChatGPT for Sentiment Analysis of Lyme Disease in Scientific Literature.

Methods in molecular biology (Clifton, N.J.)
This chapter presents a practical guide for conducting sentiment analysis using Natural Language Processing (NLP) techniques in the domain of tick-borne disease text. The aim is to demonstrate the process of how the presence of bias in the discourse ...

Does Pollyanna hypothesis hold true in death narratives? A sentiment analysis approach.

Acta psychologica
Pollyanna hypothesis claims that human beings have a universal tendency to use positive words more frequently and broadly than negative words. The present study aims to test Pollyanna hypothesis in medical death narratives at both lexical and text le...