Home »
Academic Articles & Research Papers
Showing 20 of 739 academic articles
Hind Alamro, Takashi Gojobori, Magbubah Essack, Xin Gao • Scientific Reports
(2024)
Abstract The rapid increase in biomedical publications necessitates efficient systems to automatically handle Biomedical Named Entity Recognition (BioNER) tasks in unstructured text. However, accurately detecting biomedical entities is quit...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-024-58334-x
Arlene Casey, Emma Davidson, Michael Poon, Hang Dong et al. • BMC Medical Informatics and Decision Making
(2021)
BACKGROUND: Natural language processing (NLP) has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology reports. Understanding recent developments in NLP application to r...
OPENALEX
cc-by
DOI: https://doi.org/10.1186/s12911-021-01533-7
PMC: 8176715
Cristian Cosentino, Simone Gatto, Pietro Liò, Fabrizio Marozzo • Future Internet
(2026)
Machine Learning (ML) models trained on large-scale datasets learn useful predictive patterns, but they may also memorize undesired information, leading to risks such as information leakage, bias, copyright violations, and privacy attacks. ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/fi18030174
Andrea Cadeddu, Alessandro Chessa, Vincenzo De Leo, Gianni Fenu et al. • Information
(2024)
Online platforms have become the primary means for travellers to search, compare, and book accommodations for their trips. Consequently, online platforms and revenue managers must acquire a comprehensive comprehension of these dynamics to f...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/info15070398
Chengwei Qin, Aston Zhang, Zhuosheng Zhang, Jiaao Chen et al. • Conference on Empirical Methods in Natural Language Processing (EMNLP)
(2023)
Spurred by advancements in scale, large language models (LLMs) have demonstrated the ability to perform a variety of natural language processing (NLP) tasks zero-shot-i.e., without adaptation on downstream data.Recently, the debut of ChatGP...
OPENALEX
cc-by
DOI: https://doi.org/10.18653/v1/2023.emnlp-main.85
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
Kealeboga Aiseng • Emerging Media
(2026)
This study examines the influence of artificial intelligence (AI)-driven media platforms on South Africa's indigenous languages—Setswana, Tshivenda, and Xitsonga—in the country's diverse linguistic environment. It examines how algorithmic b...
DOAJ
Open Access (DOAJ)
DOI: 10.1177/27523543261447913
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
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
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
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
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
Shijie Chen, Yu Zhang, Qiang Yang • ACM Computing Surveys
(2024)
Deep learning approaches have achieved great success in the field of Natural Language Processing (NLP). However, directly training deep neural models often suffer from overfitting and data scarcity problems that are pervasive in NLP tasks. ...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3663363
Julia El Zini, Mariette Awad • ACM Computing Surveys
(2022)
Despite their success, deep networks are used as black-box models with outputs that are not easily explainable during the learning and the prediction phases. This lack of interpretability is significantly limiting the adoption of such model...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3529755
Dheya Mustafa, Safaa M. Khabour, Mousa Al-kfairy, Ahmed Shatnawi • PeerJ Computer Science
(2025)
Companies that deliver food (food delivery services, or FDS) try to use customer feedback to identify aspects where the customer experience could be improved. Consumer feedback on purchasing and receiving goods via online platforms is a cru...
DOAJ
Open Access (DOAJ)
DOI: 10.7717/peerj-cs.2669
Miao Jiang, Honghui Chen • Applied Sciences
(2025)
Chinese named entity recognition (NER) is a fundamental natural language processing (NLP) task that involves identifying and categorizing entities in text. It plays a crucial role in applications such as information extraction, machine tran...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app15052521
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
Mehdi Yekrangi, Nikola S. Nikolov • IEEE Access
(2023)
Although different studies are caried out by deep learning models for financial markets sentiment analysis, there is a lack of specific embedding method that regards the domain. Therefore, the goal of this study is to discover what type of ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3293733
Gaurav Mohindru, Koushik Mondal, Haider Banka • CAAI Transactions on Intelligence Technology
(2021)
Abstract In the era of automatic task processing or designing complex algorithms, to analyse data, it is always pertinent to find real‐life solutions using cutting‐edge tools and techniques to generate insights into the data. The data‐drive...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/cit2.12032
Mark Neumann, Daniel King, Iz Beltagy, Waleed Ammar • BioNLP Workshop and Shared Task (BioNLP)
(2019)
Despite recent advances in natural language processing, many statistical models for processing text perform extremely poorly under domain shift. Processing biomedical and clinical text is a critically important application area of natural l...
OPENALEX
cc-by
DOI: https://doi.org/10.18653/v1/w19-5034