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Showing 20 of 193 academic articles

Natural language processing for information assurance and security

Mikhail J. Atallah, Craig Jerome Mcdonough, Victor Raskin, Sergei Nirenburg • New Security Paradigms Workshop (2001)

This research paper explores a promising interface between natural language processing (NLP) and information assurance and security (IAS). More specificall~ it is devoted to possible applications to, and further dedicated development of, th...

OPENALEX DOI: https://doi.org/10.1145/366173.366190

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

Tianlin Zhang, Annika Marie Schoene, Shaoxiong Ji, Sophia Ananiadou • npj Digital Medicine (2022)

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...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41746-022-00589-7 PMC: 8993841

BERT applications in natural language processing: a review

Nadia Mushtaq Gardazi, Ali Yusny Daud, Muhammad Kamran Malik, Amal Abdullah Bukhari et al. • Artificial Intelligence Review (2025)

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...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1007/s10462-025-11162-5

Natural Language Processing

Srikanth Machiraju, Ritesh Modi • Apress eBooks (2017)

Natural language processing (NLP) is a field of computer science that is a subset of artificial intelligence and that helps computers understand human language as it is written and spoken. Until recently, it was humans who were trying to un...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-3312-2_9

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

Seyedmostafa Sheikhalishahi, Riccardo Miotto, Joel T. Dudley, Alberto Lavelli et al. • JMIR Medical Informatics (2019)

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...

OPENALEX cc-by DOI: https://doi.org/10.2196/12239 PMC: 6528438

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

Mosima A. Masethe, Sunday O. Ojo, Hlaudi D. Masethe • Computers (2025)

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 ...

DOAJ Open Access (DOAJ) DOI: 10.3390/computers14090402

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

Arezo Shakeri, Mina Farmanbar • Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring (2025)

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...

DOAJ Open Access (DOAJ) DOI: 10.1002/dad2.70082

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

Aysenur Arpaci, Asel Usdat Ozturk, Ismail Okur, Sanaz Sadry • BMC Oral Health (2025)

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...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12903-025-06624-9

ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing

Mark Neumann, Daniel King, Iz Beltagy, Waleed Ammar • BioNLP Workshop and Shared Task (BioNLP) (2019)

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...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/w19-5034

Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing

裕二 池谷, Robert Tinn, Hao Cheng, MICHAEL A. LUCAS et al. • ACM Transactions on Computing for Healthcare (2021)

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...

OPENALEX Open Access DOI: https://doi.org/10.1145/3458754

A Systematic Review of Natural Language Processing in Healthcare

Olaronke G. Iroju, Olaleke Janet • International Journal of Information Technology and Computer Science (2015)

The healthcare system is a knowledge driven industry which consists of vast and growing volumes of narrative information obtained from discharge summaries/reports, physicians case notes, pathologists as well as radiologists reports.This inf...

OPENALEX Open Access DOI: https://doi.org/10.5815/ijitcs.2015.08.07

Natural language processing of lyrics

Jose P. G. Mahedero, Álvaro Parafita Martínez, Pedro Cano, Markus Koppenberger et al. • ACM International Conference on Multimedia (ACM MM) (2005)

We report experiments on the use of standard natural language processing (NLP) tools for the analysis of music lyrics. A significant amount of music audio has lyrics. Lyrics encode an important part of the semantics of a song, therefore the...

OPENALEX DOI: https://doi.org/10.1145/1101149.1101255

Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton et al. • Annual Meeting of the Association for Computational Linguistics: System Demonstrations (ACL Demo) (2020)

We introduce Sta n z a , an open-source Python natural language processing toolkit supporting 66 human languages.Compared to existing widely used toolkits, Sta n z a features a language-agnostic fully neural pipeline for text analysis, incl...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/2020.acl-demos.14

A Survey on Gender Bias in Natural Language Processing

Karolina Stańczak, Isabelle Augenstein • arXiv (Cornell University) (2021)

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. ...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.2112.14168