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Natural Language Processing Techniques for Text Classification of Biomedical Documents: A Systematic Review

Cyrille YetuYetu Kesiku, Andrea Chaves-Villota, Begonya Garcia-Zapirain • Information (2022)

The classification of biomedical literature is engaged in a number of critical issues that physicians are expected to answer. In many cases, these issues are extremely difficult. This can be conducted for jobs such as diagnosis and treatmen...

DOAJ Open Access (DOAJ) DOI: 10.3390/info13100499

Unlocking Clinical Data from Narrative Reports: A Study of Natural Language Processing

George M. Hripcsak, Carol Friedman, Philip O. Alderson, William DuMouchel et al. • Annals of Internal Medicine (1995)

OBJECTIVE: To evaluate the automated detection of clinical conditions described in narrative reports. DESIGN: Automated methods and human experts detected the presence or absence of six clinical conditions in 200 admission chest radiograph ...

OPENALEX DOI: https://doi.org/10.7326/0003-4819-122-9-199505010-00007

Advancements in natural language processing: Implications, challenges, and future directions

Supriyono Supriyono, Aji Prasetya Wibawa, Suyono Suyono, Fachrul Kurniawan • Telematics and Informatics Reports (2024)

This research delves into the latest advancements in Natural Language Processing (NLP) and their broader implications, challenges, and future directions. With the ever-increasing volume of text data generated daily from diverse sources, ext...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.teler.2024.100173

Natural Language Processing in Psychiatry

David Garfield, CHARLES RAPP, Martha W. Evens • The Journal of Nervous and Mental Disease (1992)

The potential benefit of artificial intelligence (AI) technology as a tool of psychiatry has not been well defined. In this essay, the technology of natural language processing and its position with regard to the two main schools of AI is c...

OPENALEX DOI: https://doi.org/10.1097/00005053-199204000-00004

Application of Convolutional Neural Network in Natural Language Processing

Wei Wang, Jianxun Gang • IEEE International Conference on Information Systems and Computer Aided Education (ICISCAE) (2018)

Convolutional neural network (Convolutionl Neural Network, CNN) is a multiple-layer neural network method to learn hierarchical characteristic of data. In recent years, CNN has developed rapidly in the design and calculation of natural lang...

OPENALEX DOI: https://doi.org/10.1109/iciscae.2018.8666928

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

Natural Language Processing Technologies in Radiology Research and Clinical Applications

Tianrun A. Cai, Andreas A. Giannopoulos, Sheng Yu, Tatiana Kelil et al. • Radiographics (2016)

The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. How...

OPENALEX Open Access DOI: https://doi.org/10.1148/rg.2016150080 PMC: 4734053

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

Incremental natural language processing for HRI

Timothy R. Brick, Matthias J. Scheutz • ACM/IEEE International Conference on Human-Robot Interaction (HRI) (2007)

Robots that interact with humans face-to-face using natural language need to be responsive to the way humans use language in those situations. We propose a psychologically-inspired natural language processing system for robots which perform...

OPENALEX DOI: https://doi.org/10.1145/1228716.1228752

Social network X and mental health in Brazil in times of coronavirus

Thallys da Silva Nogueira, Laisa Marcorela Andreoli Sarte, Priscila Vanessa Zabala Capriles Goliatt • HU Revista (2024)

Introduction: The COVID-19 pandemic has had a number of impacts on people's daily lives around the world. The radical change in people's daily routines has led to an increase in the use and consumption of social media content. The scenario ...

DOAJ Open Access (DOAJ) DOI: 10.34019/1982-8047.2024.v50.44375

A Survey of the Application of Neural Networks to Event Extraction

Jianye Xie, Yulan Zhang, Huaizhen Kou, Xiaoran Zhao et al. • Tsinghua Science and Technology (2025)

Event extraction is an important part of natural language information extraction, and it’s widely employed in other natural language processing tasks including question answering and machine reading comprehension. However, there is a lack o...

DOAJ Open Access (DOAJ) DOI: 10.26599/TST.2023.9010139

AI-generated draft replies to patient messages: exploring effects of implementation

Charlotte M. H. H. T. Bootsma-Robroeks, Charlotte M. H. H. T. Bootsma-Robroeks, Jessica D. Workum, Jessica D. Workum et al. • Frontiers in Digital Health (2025)

IntroductionThe integration of Large Language Models (LLMs) in Electronic Health Records (EHRs) has the potential to reduce administrative burden. Validating these tools in real-world clinical settings is essential for responsible implement...

DOAJ Open Access (DOAJ) DOI: 10.3389/fdgth.2025.1588143