Academic Articles & Research Papers

Mapping inequities in global vaccine sentiment research

Introduction Negative public sentiment towards vaccination (PSV) poses significant challenges to the effectiveness of immunisation programmes, with dramatic effects on morbidity and mortality for vaccine-preventable diseases. Yet, health re...

On natural language processing and plan recognition

The research areas of plan recognition and natural language parsing share many common features and even algorithms. However, the dialog between these two disciplines has not been effective. Specifically, significant recent results in parsin...

Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review

BACKGROUND: Novel approaches that complement and go beyond evidence-based medicine are required in the domain of chronic diseases, given the growing incidence of such conditions on the worldwide population. A promising avenue is the seconda...

Multi-Task Learning in Natural Language Processing: An Overview

Deep learning approaches have achieved great success in the field of Natural Language Processing (NLP). However, directly training deep neural models often suffer from overfitting and data scarcity problems that are pervasive in NLP tasks. ...

Development and evaluation of Retrieval-Augmented Generation (RAG) and GraphRAG for guideline-based clinical decision support in chronic kidney disease.

Leveraging sentiment analysis of food delivery services reviews using deep learning and word embedding

Companies that deliver food (food delivery services, or FDS) try to use customer feedback to identify aspects where the customer experience could be improved. Consumer feedback on purchasing and receiving goods via online platforms is a cru...

Label-Guided Data Augmentation for Chinese Named Entity Recognition

Chinese named entity recognition (NER) is a fundamental natural language processing (NLP) task that involves identifying and categorizing entities in text. It plays a crucial role in applications such as information extraction, machine tran...

Natural language processing in Alzheimer's disease research: Systematic review of methods, data, and efficacy

Abstract INTRODUCTION Alzheimer's disease (AD) prevalence is increasing, with no current cure. Natural language processing (NLP) offers the potential for non‐invasive diagnostics, social burden assessment, and research advancements in AD. M...

Revenue-sensitive evaluation of AI-assisted ICD-10-CM coding and human-AI collaboration under dual DRG payment systems

Abstract Automated ICD-10-CM coding is critical for hospital reimbursement under Diagnosis-Related Group (DRG) payment systems, yet standard metrics weight all errors equally. This study evaluated 11 models on MIMIC-IV under heterogeneous c...

A Deep Backtracking Bare‐Bones Particle Swarm Optimisation Algorithm for High‐Dimensional Nonlinear Functions

ABSTRACT The challenge of optimising multimodal functions within high‐dimensional domains constitutes a notable difficulty in evolutionary computation research. Addressing this issue, this study introduces the Deep Backtracking Bare‐Bones P...

Domain-Specific Sentiment Analysis: An Optimized Deep Learning Approach for the Financial Markets

Although different studies are caried out by deep learning models for financial markets sentiment analysis, there is a lack of specific embedding method that regards the domain. Therefore, the goal of this study is to discover what type of ...

Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing

In 2005, the Human Language Technology Conference (HLT) and the Conference on Empirical Methods in Natural Language Processing (EMNLP) were held together as a joint conference for the first time. The conference was co-sponsored by the organ...

ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing

Despite recent advances in natural language processing, many statistical models for processing text perform extremely poorly under domain shift. Processing biomedical and clinical text is a critically important application area of natural l...

Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]

Natural language processing (NLP) is a theory-motivated range of computational techniques for the automatic analysis and representation of human language. NLP research has evolved from the era of punch cards and batch processing (in which t...

Digital footprints as a tool to evaluate the spatiotemporal environmental impacts of grocery shopping across Great Britain

Introduction & Background Climate change represents one of the most pressing challenges of our time. Within this context, the food sector is a critical domain for intervention, accounting for approximately one-third of global greenhouse gas...

A natural language processing based technique for sentiment analysis of college english corpus

The college English corpus can help us better master English, but how to obtain the desired information from a large number of English corpus has become the focus of information technology. Based on the natural language processing (NLP) tec...

State of Art for Semantic Analysis of Natural Language Processing

Semantic analysis is an essential feature of the NLP approach. It indicates, in the appropriate format, the context of a sentence or paragraph. Semantics is about language significance study. The vocabulary used conveys the importance of th...

Bovine AAV: A promising vector for pulmonary gene therapy.

Empowering text classification with NLP and explainable AI for enhanced interpretability

Abstract Artificial intelligence (AI) models have demonstrated significant success in classifying various types of text. However, the complex nature of these models often complicates the interpretability of their classifications. To address...

USDA-SoyWheOatBar-3K: a robust high-throughput genotyping platform to accelerate molecular breeding in small grains.