Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Abstract: Text classification is fundamental in Natural Language Processing (NLP), and the advent of Large Language Models (LLMs) has revolutionized the field. This paper introduces an adaptable and ...

Abstract: Deep learning models have greatly improved various natural language processing tasks. However, their effectiveness depends on large data sets, which can be difficult to acquire. To mitigate ...

This is a Natural Language Processing (NLP) application that provides comprehensive analysis of text input, including various statistics and visualizations. The application is available both as a ...

Search engines have come a long way from relying on exact match keywords. Today, they try to understand the meaning behind content — what it says, how it says it, and whether it truly answers the ...

Background: Free-text comments in patient-reported outcome measures (PROMs) data provide insights into health-related quality of life (HRQoL). However, these comments are typically analysed using ...

We publish the best academic work (that's too often lost to peer reviews & the TA's desk) to the global tech community ...