Multilingual Sentiment Analysis for the Malaysian Healthcare Industry
About Webpage
This web application leverages cutting-edge tools like Nuxt.js, Vue.js, Bootstrap and a Long Short-Term Memory (LSTM) model to provide real-time sentiment analysis of user-provided text. Built with a Vue.js frontend, the website boasts a sleek and responsive design powered by Bootstrap. Users can input text and the application will analyze the sentiment classifying it as positive or negative. Users can also upload an excel file containing more than one input text.
On the backend, an LSTM model is trained on a vast dataset to deliver accurate predictions. This website is then hosted on Cloudflare, ensuring fast and secure content delivery, while also optimizing the site’s performance for a smooth user experience.
On the backend, an LSTM model is trained on a vast dataset to deliver accurate predictions. This website is then hosted on Cloudflare, ensuring fast and secure content delivery, while also optimizing the site’s performance for a smooth user experience.
Try out the Multilingual Sentiment Analyzer
Upload excel file if you want to do sentiment analysis on more than one text
How to do sentiment analysis on more than one textBenefit of Using Sentiment Analysis
Sentiment analysis helps healthcare providers understand patient emotion during visits, treatments or aftercare which allows better personalized care.
Sentiment analysis on patient communication can aid in detecting changes in mood or concers which enables healthcare professionals to intervene earlier.
Identify emerging health trends, such as an increase in dissatisfaction with a specific treatment or concern about a health condition.
Help doctors understand the emotional tone of their communication with their patients either face-to-face interaction, or digital platforms. This will ensure more empathetic and supportive exchanges.
Help in identifying bottlenecks or inefficiencies in hospital or clinic operations, such as poor staff communication, long waiting times, or inadequate facilities, leading to process improvements.