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Academic Articles & Research Papers
Showing 20 of 420 academic articles
Mahmoud S. Mayaleh, Samer A. Mayaleh • Discover Artificial Intelligence
(2026)
Abstract Small-scale sentiment classification often suffers from data scarcity, which limits the generalization ability of the models. This study evaluates and compares the effectiveness of three data augmentation strategies: Easy Data Augm...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44163-025-00813-9
Imran Mirza, Akbar Anbar Jafari, Cagri Ozcinar, Gholamreza Anbarjafari • Information
(2025)
Large language models (LLMs) have revolutionized natural language processing across diverse domains, yet they also raise critical fairness and ethical concerns, particularly regarding gender bias. In this study, we conduct a systematic, mat...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/info16050358
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...
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Open Access
DOI: https://doi.org/10.1148/rg.2016150080
PMC: 4734053
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...
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cc-by-nc-nd
DOI: https://doi.org/10.1038/s41524-025-01554-0
Jalaj Thanaki (2017)
Leverage the power of machine learning and deep learning to extract information from text dataAbout This BookImplement Machine Learning and Deep Learning techniques for efficient natural language processingGet started with NLTK and implemen...
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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...
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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...
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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...
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other-oa
DOI: https://doi.org/10.1063/5.0021106
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
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. ...
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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...
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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