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A bibliometric analysis of natural language processing in medical research

Xieling Chen, Haoran Xie, Fu Lee Wang, Ziqing Liu et al. • BMC Medical Informatics and Decision Making (2018)

BACKGROUND: Natural language processing (NLP) has become an increasingly significant role in advancing medicine. Rich research achievements of NLP methods and applications for medical information processing are available. It is of great sig...

OPENALEX cc-by DOI: https://doi.org/10.1186/s12911-018-0594-x PMC: 5872501

Natural Language Processing

Matthew N. O. Sadiku, Yu Ping Zhou, Sarhan M. Musa • International Journal of Advances in Scientific Research and Engineering (2018)

Natural language processing (NLP) refers to the field of study that focuses on the interactions between human language and computers. It is a computational approach to text analysis. It is the application of a wide range of computational te...

OPENALEX cc-by-nc DOI: https://doi.org/10.31695/ijasre.2018.32708

Applications of natural language processing and large language models in materials discovery

Xue Feng Jiang, Weiren Wang, Shaohan Tian, Hao Wang et al. • npj Computational Materials (2025)

The transformative impact of artificial intelligence (AI) technologies on materials science has revolutionized the study of materials problems. By leveraging well-characterized datasets derived from the scientific literature, AI-powered too...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1038/s41524-025-01554-0

Applied Natural Language Processing

Martin Hassel, Hercules Dalianis • IGI Global eBooks (2011)

Today, with digitally stored information available in abundance, even for many less commonly spoken languages, this information must by some means be filtered and extracted in order to avoid drowning in it. Automatic summarization is one su...

OPENALEX public-domain DOI: https://doi.org/10.4018/978-1-60960-741-8

Construction of a knowledge graph for the educational statistical indicator system based on large language models

WANG Pengyu, JIANG Shuming, WEI Zhiqiang, YU Jun, ZHANG Mengmeng • Shandong kexue (2026)

Current statistical work in the field of educational development faces challenges such as low knowledge-retrieval efficiency and high technical barriers to data utilization. This study focuses on the knowledge related to the indicator syste...

DOAJ Open Access (DOAJ) DOI: 10.3976/j.issn.1002-4026.2025079

DEVELOPMENT OF A QUESTION ANSWERING CHATBOT FOR BLOCKCHAIN DOMAIN

Aigerim Mansurova, Aliya Nugumanova, Zhansaya Makhambetova • Scientific Journal of Astana IT University (2023)

Large Language Models (LLMs), such as ChatGPT, have transformed the field of natural language processing with their capacity for language comprehension and generation of human-like, fluent responses for many downstream tasks. Despite their ...

DOAJ Open Access (DOAJ) DOI: 10.37943/15XNDZ6667

Semantic Alignment in Disciplinary Tutoring System: Leveraging Sentence Transformer Technology

Rosana Abdoune, Lydia Lazib, Farida Dahmani-Bouarab, Nada Mimouni • Inteligencia Artificial (2024)

In this work, we present a disciplinary e-tutoring system that integrates ONTO-TDM, an ontology designed for teaching domain modeling, with advanced transformer technology. Our primary objective is to enhance semantic similarity tasks withi...

DOAJ Open Access (DOAJ)

Understanding the regulatory grammar of sepsis-causing Staphylococcus aureus bacteria using contexualised DNA language models

Tyrone Chen, Anton Y. Peleg, Sonika Tyagi • Scientific Reports (2025)

Abstract To efficiently and accurately understand, detect, and treat sepsis, we require a deep understanding of how its underlying biological systems work. Conventional methods struggle to provide a detailed view of both the functional and ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-16701-2

Data-driven materials research enabled by natural language processing and information extraction

Elsa Olivetti, Jacqueline M. Cole, Edward Kim, Olga Kononova et al. • Applied Physics Reviews (2020)

Given the emergence of data science and machine learning throughout all aspects of society, but particularly in the scientific domain, there is increased importance placed on obtaining data. Data in materials science are particularly hetero...

OPENALEX other-oa DOI: https://doi.org/10.1063/5.0021106

Provable Limitations of Acquiring Meaning from Ungrounded Form: What Will Future Language Models Understand?

William Merrill, Yoav Goldberg, Roy Schwartz, Noah A. Smith • Transactions of the Association for Computational Linguistics (2021)

AbstractLanguage models trained on billions of tokens have recently led to unprecedented results on many NLP tasks. This success raises the question of whether, in principle, a system can ever “understand” raw text without access to some fo...

DOAJ Open Access (DOAJ) DOI: 10.1162/tacl_a_00412

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

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