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Academic Articles & Research Papers
Showing 20 of 1,656 academic articles
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
Rishi V. Parikh, Alan S. Go, Ankeet S. Bhatt, Thida C. Tan et al. • Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
(2023)
Background There is a need to develop electronic health record–based predictive models for worsening heart failure (WHF) events across clinical settings and across the spectrum of left ventricular ejection fraction (LVEF). Methods and Resul...
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Open Access (DOAJ)
DOI: 10.1161/JAHA.122.029736
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...
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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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DOI: https://doi.org/10.18653/v1/2023.emnlp-main.85
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...
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Open Access (DOAJ)
DOI: 10.1162/tacl_a_00412
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 ...
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Open Access (DOAJ)
DOI: 10.1016/j.jjimei.2024.100287
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 ...
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DOI: https://doi.org/10.2196/15708
PMC: 8132982
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...
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Open Access (DOAJ)
DOI: 10.3390/app142411897
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 ...
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Open Access (DOAJ)
DOI: 10.5771/2192-4007-2024-1-72
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...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3530949
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
Tianlin Zhang, Annika Marie Schoene, Shaoxiong Ji, Sophia Ananiadou • npj Digital Medicine
(2022)
Mental illness is highly prevalent nowadays, constituting a major cause of distress in people's life with impact on society's health and well-being. Mental illness is a complex multi-factorial disease associated with individual risk factors...
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DOI: https://doi.org/10.1038/s41746-022-00589-7
PMC: 8993841
Nadia Mushtaq Gardazi, Ali Yusny Daud, Muhammad Kamran Malik, Amal Abdullah Bukhari et al. • Artificial Intelligence Review
(2025)
BERT (Bidirectional Encoder Representations from Transformers) has revolutionized Natural Language Processing (NLP) by significantly enhancing the capabilities of language models. This review study examines the complex nature of BERT, inclu...
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DOI: https://doi.org/10.1007/s10462-025-11162-5
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...
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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...
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Open Access (DOAJ)
DOI: 10.3390/app15052521
Mosima A. Masethe, Sunday O. Ojo, Hlaudi D. Masethe • Computers
(2025)
Meaning conflation deficiency (MCD) presents a continual obstacle in natural language processing (NLP), especially for low-resourced and morphologically complex languages, where polysemy and contextual ambiguity diminish model precision in ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/computers14090402
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
Ming-I. Chen, Ying-Lin Hsu, Yi-Hsin Chen • Scientific Reports
(2026)
Abstract Automated ICD-10-CM coding is critical for hospital reimbursement under Diagnosis-Related Group (DRG) payment systems, yet standard metrics weight all errors equally. This study evaluated 11 models on MIMIC-IV under heterogeneous c...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-57682-0