Intrahemispheric Perfusion in Chronic Stroke-Induced Aphasia by Cynthia K. Thompson, Matthew Walenski, YuFen Chen, David Caplan, Swathi Kiran, Brenda Rapp, Kristin Grunewald, Mia Nunez, Richard Zinbarg, Todd B. Parrish

“…These patterns may reflect autoregulatory changes in blood flow following stroke and/or increases in general cognitive effort, rather than maladaptive language processing. We also examined blood flow in perilesional tissue, finding the greatest hypoperfusion close to the lesion (within 0–6 mm), with greater hypoperfusion in this region compared to more distal regions. …”
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DNA sequence classification for diabetes mellitus using NuSVC and XGBoost: A comparative. by Said A Salloum, Khaled Mohammad Alomari, Ayham Salloum

“…The dataset, obtained from reputable sources like NCBI, was preprocessed using Natural Language Processing (NLP) techniques, where DNA sequences were treated as textual data and transformed into numerical features using TF-IDF (Term Frequency-Inverse Document Frequency). …”
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Development of adaptive and emotionally intelligent educational assistants based on conversational AI by Rommel Gutierrez, William Villegas-Ch, Jaime Govea

“…To address this gap, this study proposes and evaluates an educational assistant based on conversational artificial intelligence, which integrates natural language processing, real-time emotional analysis, and dynamic cognitive adaptation. …”
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One size fits all: Enhanced zero-shot text classification for patient listening on social media by Veton Matoshi, Maria Carmela De Vuono, Roberto Gaspari, Mark Kröll, Michael Jantscher, Sara Lucia Nicolardi, Giuseppe Mazzola, Manuela Rauch, Vedran Sabol, Eileen Salhofer, Riccardo Mariani

“…Recent advancements in Artificial Intelligence (AI), especially in Natural Language Processing (NLP), have enabled the analysis of vast social media datasets, also called Social Media Listening (SML), providing insights not only into patient perspectives but also into those of other interest groups such as caregivers. …”
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Reducing hallucinations of large language models via hierarchical semantic piece by Yanyi Liu, Qingwen Yang, Jiawei Tang, Tiezheng Guo, Chen Wang, Pan Li, Sai Xu, Xianlin Gao, Zhi Li, Jun Liu, Yingyou Wen

“…Abstract With the widespread application of large language models (LLMs) in natural language processing (NLP), hallucinations have become a significant impediment to their effective use of LLMs in industry applications. …”
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Arabic Fake News Detection: Comparative Study of Neural Networks and Transformer-Based Approaches by Maha Al-Yahya, Hend Al-Khalifa, Heyam Al-Baity, Duaa AlSaeed, Amr Essam

“…However, most existing approaches do not consider recent advances in natural language processing, i.e., the use of neural networks and transformers. …”
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Automated Pruning Framework for Large Language Models Using Combinatorial Optimization by Patcharapol Ratsapa, Kundjanasith Thonglek, Chantana Chantrapornchai, Kohei Ichikawa

“…Currently, large language models (LLMs) have been utilized in many aspects of natural language processing. However, due to their significant size and high computational demands, large computational resources are required for deployment. …”
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Attention-based interactive multi-level feature fusion for named entity recognition by Yiwu Xu, Yun Chen

“…Abstract Named Entity Recognition (NER) is an essential component of numerous Natural Language Processing (NLP) systems, with the aim of identifying and classifying entities that have specific meanings in raw text, such as person (PER), location (LOC), and organization (ORG). …”
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Artificial intelligence in early warning systems for infectious disease surveillance: a systematic review by Ismael Villanueva-Miranda, Guanghua Xiao, Guanghua Xiao, Yang Xie, Yang Xie

“…After screening 600 records and removing duplicates and non-relevant articles, the search yielded 67 relevant studies for review.ResultsKey findings reveal the prevalent use of machine learning (ML), deep learning (DL), and natural language processing (NLP), which often integrate diverse data sources (e.g., epidemiological, web, climate, wastewater). …”
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Terminology Alignment based on Multi-level Feature Fusion for Japanese Scientific and Technological Literature Terminology Translation by Qi Fang

“…Bilingual terminology alignment databases represent crucial resources in the field of natural language processing, holding significant value for multilingual applications such as cross-lingual information retrieval and machine translation. …”
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Enhancing counterfactual detection in multilingual contexts using a few shot clue phrase approach by Lekshmi Kalinathan, Karthik Raja Anandan, Jagadish Ravichandran, K. Devi, S. Benila, Abithkumar Ravikumar

“…The incorporation of clue-phrases during training not only addresses the issue of limited data but also significantly boosts the model’s capability in accurately identifying counterfactual statements, thereby offering a more effective solution in this challenging area of natural language processing.…”
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Mindful Architecture from Text-to-Image AI Perspectives: A Case Study of DALL-E, Midjourney, and Stable Diffusion by Chaniporn Thampanichwat, Tarid Wongvorachan, Limpasilp Sirisakdi, Pornteera Chunhajinda, Suphat Bunyarittikit, Rungroj Wongmahasiri

“…These words were then analyzed using natural language processing techniques, including Word Cloud Generation, Word Frequency Analysis, and Topic Modeling Analysis. …”
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Research trends in artificial intelligence in English language teaching (ELT): A bibliometric analysis by Didin Nuruddin Hidayat, Syahrul Ramadhan, Mahlil Mahlil, Jon Mason, Rodi Hartono, Afif Ikhwanul Muslimin

“…Co-occurrence network analysis further underscores the interconnectedness of various research topics, such as machine learning, natural language processing, and autonomous learning systems. The growing body of research indicates that AI technologies are increasingly being integrated into educational practices, offering more personalized, efficient, and engaging learning experiences. …”
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Relation Semantic Guidance and Entity Position Location for Relation Extraction by Guojun Chen, Panfeng Chen, Hui Li, Xibin Wang, Xin Zhou, Aihua Yu, Xingzhi Deng, Qi Wang

“…Abstract Relation extraction is a research hot-spot in the field of natural language processing, and aims at structured knowledge acquirement. …”
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Essential Oils and Extracts from Epazote (<i>Dysphania ambrosioides</i>): A Phytochemical Treasure with Multiple Applications by Arsenio Heredia Severino, Juana Fernández-López, Fernando Borrás-Rocher, Manuel Viuda-Martos

“…To select the most relevant articles, this AI tool based on natural language processing (available online and free of charge) was applied, which analyzed the keywords that appeared in the titles and abstracts of the works and clustered them, leading to a reduction of 86.73% in the number of studies. …”
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HANA: An AI Chatbot for Islamic Jurisprudence on Menstruation using SBERT and TF-IDF by Tsaura Rafah Masuzzahra, Khothibul Umam, Hery Mustofa, Maya Rini Handayani

“…The advancement of Artificial Intelligence (AI), particularly in Natural Language Processing (NLP), has opened new opportunities for religious technological innovation, especially in addressing practical Islamic jurisprudence issues such as menstruation (fiqh haid). …”
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Reduced Forgetfulness in Continual Learning for Named Entity Recognition Through Confident Soft-Label Imitation by Huan Zhang, Long Zhou, Miaomiao Gu

“…Continual Learning for Named Entity Recognition (CL-NER) is a crucial task in recognizing emerging concepts when constructing real-world natural language processing applications. It involves sequentially updating an existing NER model with new entity types while retaining previously learned information. …”
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Comparative Analysis of GPT-4 and LLaMA 3.2 Integration With Speech Processing Models for Enhancing Human&#x2013;Robot Interaction and Motion Control in Real-World Applications by Sheeba Uruj, Riddhi Goswami, Sujala D. Shetty, Kalaichelvi Venkatesan, Karthikeyan Ramanujam

“…This paper provides a comparative study of different Natural Language Processing (NLP) models that are created by combining advanced Large Language Models (LLMs) with speech processing technologies to create a more intuitive, adaptable, and accurate system for robots. …”
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Incorporating echo state network and sand cat swarm optimization algorithm based on quantum for named entity recognition by Fang Huang, Baocheng Wang, Jafar Safarzadeh

“…Abstract Named entity recognition (NER) has been seen as a fundamental component for various natural language processing (NLP) tasks, such as extracting information and answering questions. …”
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ALGORITHMIC PROCEDURES OF IDENTIFYING ADVERTISEMENT TEXTS IN MASS MEDIA DISCOURSE by Mikhail V. Kamensky, Sergey N. Bredikhin

“…This proves the effectiveness of natural language processing systems in identifying messages with explicit and implicit advertisement content, determining the discursive type of media texts, and classifying them as either informative texts or advertisements.…”
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