Academic Articles & Research Papers

Menstrual Health Education Using a Specialized Large Language Model in India: Development and Evaluation Study of MenstLLaMA

Abstract BackgroundThe quality and accessibility of menstrual health education (MHE) in low- and middle-income countries, including India, remain inadequate due to persistent challenges (eg, poverty, social stigma, and gender in...

Natural language processing applied to mental illness detection: a narrative review

Mental illness is highly prevalent nowadays, constituting a major cause of distress in people's life with impact on society's health and well-being. Mental illness is a complex multi-factorial disease associated with individual risk factors...

BERT applications in natural language processing: a review

BERT (Bidirectional Encoder Representations from Transformers) has revolutionized Natural Language Processing (NLP) by significantly enhancing the capabilities of language models. This review study examines the complex nature of BERT, inclu...

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. ...

On the Explainability of Natural Language Processing Deep Models

Despite their success, deep networks are used as black-box models with outputs that are not easily explainable during the learning and the prediction phases. This lack of interpretability is significantly limiting the adoption of such model...

Mapping the monthly habitat dynamics of greater amberjack using MaxEnt model in the Taiwan Strait: Implications for sustainable blue transformations.

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...

Optimising Contextual Embeddings for Meaning Conflation Deficiency Resolution in Low-Resourced Languages

Meaning conflation deficiency (MCD) presents a continual obstacle in natural language processing (NLP), especially for low-resourced and morphologically complex languages, where polysemy and contextual ambiguity diminish model precision in ...

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...

Gender biases in GPT-4 short biographies.

As has been shown in various studies considering different languages, in professional contexts women tend to be referred to differently than men. While men are typically referred to by their surname (e. g., Fermi), women are more often refe...

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 ...

SAM-trace: a fuzzy logic approach in identifying interaction effects in the exacerbation of childhood malnutrition severity

Abstract Pediatric malnutrition remains a major global health challenge. Conventional WHO-based binary classification (Severe Acute Malnutrition (SAM) / Moderate Acute Malnutrition (MAM) relies solely on anthropometric thresholds. It fails ...

Evaluation of the accuracy of ChatGPT-4 and Gemini’s responses to the World Dental Federation’s frequently asked questions on oral health

Abstract Background The field of artificial intelligence (AI) has experienced considerable growth in recent years, with the advent of technologies that are transforming a range of industries, including healthcare and dentistry. Large langua...

Different hybrid machine intelligence techniques for handling IoT‐based imbalanced data

Abstract In the era of automatic task processing or designing complex algorithms, to analyse data, it is always pertinent to find real‐life solutions using cutting‐edge tools and techniques to generate insights into the data. The data‐drive...

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...

Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing

Pretraining large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. However, most pretraining efforts focus on general domain corpora, such as newswire and Web. A prevailing a...

A Survey on Gender Bias in Natural Language Processing

Language can be used as a means of reproducing and enforcing harmful stereotypes and biases and has been analysed as such in numerous research. In this paper, we present a survey of 304 papers on gender bias in natural language processing. ...

Evolutionary Constraints Improve Protein Large Language Model Predictions for Protein Stability, Binding Regions, and Epistasis.