Moving cannabis to a category of drugs that includes some common medicines will have implications for research, businesses and patients. By Jan Hoffman President Trump on Thursday ordered cannabis to ...

Abstract: This review article provides a thorough assessment of modern and innovative algorithms for text classification through both observational and experimental evaluations. We propose a new ...

ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...

A web-based AI-powered Sentiment Analyzer that uses VADER, ROBERTa and BERT models to detect positive, negative, or neutral sentiment in text. Built with Flask and NLP tools, it's perfect for ...

ABSTRACT: Pregnancy presents a unique clinical scenario where the safety of pharmacological interventions is of paramount importance. The potential teratogenic risks associated with drug intake during ...

Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...

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 ...

Large Language Models (LLMs) ushered in a technological revolution. We breakdown how the most important models work. Large Language Models (LLMs) ushered in a technological revolution. We breakdown ...

In recent decades, medical short texts, such as medical conversations and online medical inquiries, have garnered significant attention and research. The advances in the medical short text have ...

Abstract: We propose a text classification model based on dependency graph attention convolution, which improves the model’s accurate recognition of the text category by mining the semantic features ...