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Showing 20 of 962 academic articles

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

Natural Language Processing

Ralph Weischedel, J Carbonell, Barbara J. Grosz, W. Lehnert et al. • Annual Review of Computer Science (1990)

From the Publisher: These ten contributions describe the major technical ideas underlying many of the significant advances in natural language processing over the last decade, focusing in particular on the challenges in areas such as knowl...

OPENALEX DOI: https://doi.org/10.1146/annurev.cs.04.060190.002251

Data augmentation techniques in natural language processing

Lucas Francisco Amaral Orosco Pellicer, Taynan Maier Ferreira, Anna Helena Reali Costa • Applied Soft Computing (2022)

Data Augmentation (DA) methods – a family of techniques designed for synthetic generation of training data – have shown remarkable results in various Deep Learning and Machine Learning tasks. Despite its widespread and successful adoption w...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.asoc.2022.109803

Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets

Michał Wawer, Jarosław A. Chudziak, Ewa Niewiadomska-Szynkiewicz • Applied Sciences (2024)

Traditional technical analysis methods face limitations in accurately predicting trends in today’s complex financial markets. Meanwhile, existing AI-driven approaches, while powerful in processing large datasets, often lack interpretability...

DOAJ Open Access (DOAJ) DOI: 10.3390/app142411897

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

Few-shot learning for automated content analysis: Efficient coding of arguments and claims in the debate on arms deliveries to Ukraine

Jonas Rieger, Kostiantyn Yanchenko, Mattes Ruckdeschel, Gerret von Nordheim et al. • Studies in Communication, Media (2024)

Pre-trained language models (PLM) based on transformer neural networks developed in the field of natural language processing (NLP) offer great opportunities to improve automatic content analysis in communication science, especially for the ...

DOAJ Open Access (DOAJ) DOI: 10.5771/2192-4007-2024-1-72

MFSM: Chinese-English sentence alignment based on multi- feature self-attention mechanism fusion

Baolong Li • Journal of Applied Science and Engineering (2025)

Bilingual parallel corpora is a very important basic resource in the research field of natural language processing based on statistics. There are cross alignment and empty alignment in Chinese-English bilingual text, it is easy to affect th...

DOAJ Open Access (DOAJ) DOI: 10.6180/jase.202510_28(10).0005

Analyzing Sentiments in eLearning: A Comparative Study of Bangla and Romanized Bangla Text Using Transformers

Md Akash Rahman, Manoara Begum, Tanjim Mahmud, Mohammad Shahadat Hossain et al. • IEEE Access (2024)

In the modern world, learning is becoming increasingly critical due to rapid technological breakthroughs, which highlight the need for continuous skill development in both the personal and professional spheres. As a result, eLearning is a c...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3419024

Machine Reading Comprehension for the Tamil Language With Translated SQuAD

Anton Vijeevaraj Ann Sinthusha, Eugene Y. A. Charles, Ruvan Weerasinghe • IEEE Access (2025)

Machine Reading Comprehension (MRC) is a challenging task in Natural Language Processing (NLP), crucial for automated customer support, enabling chatbots and virtual assistants to accurately understand and respond to queries. It also enhanc...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3530949

Research on application of GPS-based wireless communication system in highway landslide

Zhiwen Xiong • EURASIP Journal on Wireless Communications and Networking (2021)

Abstract Machine learning is a branch of the field of artificial intelligence. Deep learning is a complex machine learning algorithm that has unique advantages in image recognition, speech recognition, natural language processing, and indus...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13638-021-02038-7