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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...
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DOI: https://doi.org/10.1109/iciscae.2018.8666928
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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DOI: https://doi.org/10.1038/s41524-025-01554-0
Francesco Maria Cianciaruso • Discover Artificial Intelligence
(2026)
Abstract The increasingly rapid development of deep learning algorithms is radically transforming society. The potential of neural models is paving the way for the automation of areas previously unrelated to AI, from medical diagnostics to ...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44163-026-01111-8
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...
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Open Access (DOAJ)
DOI: 10.1038/s41598-024-58334-x
Leanne Nortje, Dan Oneaţă, Yevgen Matusevych, Herman Kamper • Transactions of the Association for Computational Linguistics
(2024)
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Open Access (DOAJ)
DOI: 10.1162/tacl_a_00672
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 ...
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Open Access (DOAJ)
DOI: 10.34019/1982-8047.2024.v50.44375
Sargam Yadav, Abhishek Kaushik, Kevin McDaid • Applied AI Letters
(2026)
ABSTRACT Although artificial intelligence (AI) models have demonstrated great success and efficiency in automatically countering online hate speech and misogyny, they suffer from a lack of explainability and transparency. Explainable artifi...
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Open Access (DOAJ)
DOI: 10.1002/ail2.70028
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...
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Open Access (DOAJ)
DOI: 10.26599/TST.2023.9010139
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...
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Open Access (DOAJ)
DOI: 10.3389/fdgth.2025.1588143
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...
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Open Access (DOAJ)
DOI: 10.3976/j.issn.1002-4026.2025079
Zhewei Zhang, Huzi Cheng, Tianming Yang • PLoS Computational Biology
(2020)
The brain makes flexible and adaptive responses in a complicated and ever-changing environment for an organism's survival. To achieve this, the brain needs to understand the contingencies between its sensory inputs, actions, and rewards. Th...
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Open Access (DOAJ)
DOI: 10.1371/journal.pcbi.1008342
Aditya Malte, Pratik Ratadiya • arXiv (Cornell University)
(2019)
In this paper, we present a study of the recent advancements which have helped bring Transfer Learning to NLP through the use of semi-supervised training. We discuss cutting-edge methods and architectures such as BERT, GPT, ELMo, ULMFit amo...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1910.07370
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
Zhijing Jin, Rada F. Mihalcea • Springer eBooks
(2022)
Abstract Language is the medium for many political activities, from campaigns to news reports. Natural language processing (NLP) uses computational tools to parse text into key information that is needed for policymaking. In this chapter, w...
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DOI: https://doi.org/10.1007/978-3-031-16624-2_7
William J. Zeng, Bob Coecke • Electronic Proceedings in Theoretical Computer Science
(2016)
We propose a new application of quantum computing to the field of natural language processing. Ongoing work in this field attempts to incorporate grammatical structure into algorithms that compute meaning. In (Coecke, Sadrzadeh and Clark, 2...
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cc-by-nc-nd
DOI: https://doi.org/10.4204/eptcs.221.8
Singh N, Jain PK, Vohra R, Dubey AK et al. • Cardiovascular Diagnosis and Therapy
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.21037/cdt-2026-0347
PMC: PMC13735859
Asefeh Asemi, Rajab Kiani Shahvandy, Mahdi Houshangi • International Journal of Information Management Data Insights
(2026)
Objective: This study conducts a comprehensive empirical evaluation of semantic clustering algorithms to identify the most effective approach for automatically organizing and extracting meaning from textual data. By systematically comparing...
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Open Access (DOAJ)
DOI: 10.1016/j.jjimei.2026.100396
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 ...
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Open Access (DOAJ)
DOI: 10.37943/15XNDZ6667
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...
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Open Access (DOAJ)
Ante Grgurevic, Marina Bagic Babac • IEEE Access
(2025)
In this paper, we introduce Vox Calculi, a system designed to solve mathematical problems using voice transcriptions. By leveraging state-of-the-art pretrained Automatic Speech Recognition (ASR) models, we accurately transcribe users’...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3564121