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Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed

Wang, Jing, Deng, Huan, Liu, Bangtao, Hu, Anbin et al. • Journal of Medical Internet Research (2020)

BackgroundNatural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and incr...

DOAJ Open Access (DOAJ) DOI: 10.2196/16816

Economic Activity Forecasting Based on the Sentiment Analysis of News

Mantas Lukauskas, Vaida Pilinkienė, Jurgita Bruneckienė, Alina Stundžienė et al. • Mathematics (2022)

The outbreak of war and the earlier and ongoing COVID-19 pandemic determined the need for real-time monitoring of economic activity. The economic activity of a country can be defined in different ways. Most often, the country’s economic act...

DOAJ Open Access (DOAJ) DOI: 10.3390/math10193461

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

Location factors and ecosystem embedding of sustainability-engaged blockchain companies in the US. A web-based analysis

Jan Kinne, Robert Dehghan, Sebastian Schmidt, David Lenz et al. • International Journal of Information Management Data Insights (2024)

While many digital technologies provide opportunities for creating business models that impact sustainability, some technologies, especially blockchain applications, are often criticized for harming the environment, e.g. due to high energy ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jjimei.2024.100287

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

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

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

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

Text Filtering through Multi-Pattern Matching: A Case Study of Wu–Manber–Uy on the Language of Uyghur

Turdi Tohti, Jimmy Huang, Askar Hamdulla, Xing Tan • Information (2019)

Given its generality in applications and its high time-efficiency on big data-sets, in recent years, the technique of text filtering through pattern matching has been attracting increasing attention from the field of information retrieval a...

DOAJ Open Access (DOAJ) DOI: 10.3390/info10080246

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

Prottay Kumar Adhikary, Isha Motiyani, Gayatri Oke, Maithili Joshi et al. • Journal of Medical Internet Research (2025)

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...

DOAJ Open Access (DOAJ) DOI: 10.2196/71977