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Showing 20 of 1,941 academic articles

Training‐Efficient Personalised Knee Joint Moment Estimation via an Incremental Broad Learning System

Guoyu Zuo, Minghui Zhang, Jingwei Ren, Qifei Wu et al. • CAAI Transactions on Intelligence Technology (2026)

ABSTRACT Knee joint moment estimation is a critical component in biomechanical analysis, with profound implications for rehabilitation assessment and the development of assistive devices like exoskeletons. However, existing data‐driven appr...

DOAJ Open Access (DOAJ) DOI: 10.1049/cit2.70165

MedScan, a natural language processing engine for MEDLINE abstracts

Svetlana Novichkova, Sergei Egorov, Nikolai Daraselia • Bioinformatics (2003)

MOTIVATION: The importance of extracting biomedical information from scientific publications is well recognized. A number of information extraction systems for the biomedical domain have been reported, but none of them have become widely us...

OPENALEX Open Access DOI: https://doi.org/10.1093/bioinformatics/btg207

Machine Learning and Natural Language Processing in Mental Health: Systematic Review

Aziliz Le Glaz, Yannis Haralambous, Deok-Hee Kim-Dufor, Philippe Lenca et al. • Journal of Medical Internet Research (2020)

BACKGROUND: Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides ...

OPENALEX cc-by DOI: https://doi.org/10.2196/15708 PMC: 8132982

Information Extraction From FDA Drug Labeling to Enhance Product-Specific Guidance Assessment Using Natural Language Processing

Yiwen Shi, Ping Ren, Yi Zhang, Xiajing Gong et al. • Frontiers in Research Metrics and Analytics (2021)

Towards the objectives of the UnitedStates Food and Drug Administration (FDA) generic drug science and research program, it is of vital importance in developing product-specific guidances (PSGs) with recommendations that can facilitate and ...

DOAJ Open Access (DOAJ) DOI: 10.3389/frma.2021.670006

Influence in the caption: how mega influencers use language in sponsored Instagram posts

Safura Mohamed Kallier-Tar, Monique Du Bruyn • Frontiers in Communication (2026)

Background/IntroductionThe success of influencer marketers' posts on social media often hinges on the influencer's ability to resonate with their audience through the language that they use. By leveraging their unique language cues and comm...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcomm.2026.1799090

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