Artificial intelligence-assisted nursing interventions in psychiatry for oral cancer patients: A concise narrative review by Abdulmalik Fareeq Saber, Sirwan Khalid Ahmed, Safin Hussein, Karzan Qurbani

“…AI-driven tools, such as predictive models, natural language processing, and mobile applications, provide novel means of early disease detection, risk assessment, personalized care planning, and real-time patient support. …”
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Japanese Short Answer Grading for Japanese Language Learners Using the Contextual Representation of BERT by Dyah Lalita Luhurkinanti, Prima Dewi Purnamasari, Takashi Tsunakawa, Anak Agung Putri Ratna

“…Bidirectional encoder representations from transformer (BERT), which has shown potential for natural language processing (NLP) tasks, is implemented to grade answers without fine-tuning due to the small amount of data. …”
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Investigating Valency Decreasing Verb Operational Devices: A Case Study of the Oromo Language by Ayub Ismael Jarso, Giorgio Banti

“…This study seeks to contribute to (i) providing a comprehensive analysis of valency-decreasing mechanisms in the Oromo language; (ii) identifying universal patterns or language-specific variations in valency decrease strategies; (iii) informing linguistic theories by examining how operational devices impact verb valency; (iv) offering insights for language documentation, language teaching, and natural language processing (NLP) systems.…”
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Healthcare research and development (R&D) as reflected in digital news: Analysis from Kenya, Nigeria, and South Africa by Emily Ndulue, Sandra Roberts, Praise Abraham

“…These were analysed using both computational natural language processing (NLP) and manual qualitative analysis. …”
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A Client-Centric Evaluation System to Evaluate Guest’s Satisfaction on Airbnb Using Machine Learning and NLP by Mohamed Chiny, Omar Bencharef, Moulay Youssef Hadi, Younes Chihab

“…So, we applied natural language processing (NLP) algorithms to the reviews in order to find clues that could help us segment them, and then we trained two regression models, multiple linear regression and support vector regression, in order to calculate the coefficients acting on each of the 6 elementary scores (precision, cleanliness, check-in, communication, location, and value) noted on Airbnb, taking into account the category of customers who evaluated the performance of their accommodation. …”
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Climate adaptation plans and “green jobs”: challenges for implementing a responsive, multi-skilled workforce in Worcester, Massachusetts by Varun Bhat, Sarah Strauss

“…We conduct this analysis with the help of natural language processing and qualitative coding in the City of Worcester, Massachusetts, USA using job data from Indeed and semi-structured interviews. …”
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LEXICOGRAPHIC PROBLEMS OF MACHINE TRANSLATION SYSTEMS ON THE WAY FROM LITERAL TO NEURAL by Larisa N. Beliaeva, Olga N. Kamshilova

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SynoExtractor: A Novel Pipeline for Arabic Synonym Extraction Using Word2Vec Word Embeddings by Rawan N. Al-Matham, Hend S. Al-Khalifa

“…Automatic synonym extraction plays an important role in many natural language processing systems, such as those involving information retrieval and question answering. …”
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Knowledge Graph Completion With Pattern-Based Methods by Maryam Sabet, Mohammadreza Pajoohan, Mohammad Reza Moosavi

“…The first phase utilizes multi-source information and expands the KG using entity description as external information with efficient Natural Language Processing (NLP) techniques. In the second phase, we mine frequent patterns from the expanded KG, extract connections between them and assign entities to the patterns that construct the abstraction layer. …”
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Screening of multi deep learning-based de novo molecular generation models and their application for specific target molecular generation by Yishu Wang, Mengyao Guo, Xiaomin Chen, Dongmei Ai

“…In particular, the emergence of a novel natural language processing (NLP) architecture called the transformer has improved the state-of-the-art performance of existing AI technologies. …”
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Word Vector Representation of Latin Cuengh Based on Root Feature Enhancement by Weibin Lyu, Jinlong Chen, Xingguo Qin, Jun Li

“…Word vector representation is the basic method and an important foundation of current research on natural language processing. It relies on a large number of data resources and is obtained through the paradigm of pre-training and feature learning. …”
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Designing a Knowledge-Based Chatbot to Elevate Business Licensing Services in Indonesia by Husain Husain, Ridwan Afandi, Dana Indra Sensuse, Sofian Lusa, Nadya Safitri, Damayanti Elisabeth

“…The proposed chatbot will utilize natural language processing (NLP) technology and a structured knowledge base to provide accurate information, assist in form filling, and offer step-by-step guidance to users. …”
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T-LLaMA: a Tibetan large language model based on LLaMA2 by Hui Lv, Chi Pu, La Duo, Yan Li, Qingguo Zhou, Jun Shen

“…To our knowledge, T-LLaMA stands as the first large-scale language model in Tibetan natural language processing (NLP) with parameters in the billion range. …”
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Deteksi Cyberbullying dengan Mesin Pembelajaran Klasifikasi (Supervised Learning): Peluang dan Tantangan by Yudi Setiawan, Nur Ulfa Maulidevi, Kridanto Surendro

“…Penelitian deteksi pola dan karakteristik cyberbullying banyak dilakukan dengan berbagai metode, seperti dengan mengimplementasikan Machine Learning, Natural Language Processing (NLP), dan Sentiment Analysis yang memiliki variasi akurasi yang berbeda, dengan keunggulan dan kelemahan dari masing-masing metode. …”
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Recognition model for major depressive disorder in Arabic user-generated content by Esraa M. Rabie, Atef F. Hashem, Fahad Kamal Alsheref

“…This research offers a novel framework for depression detection from Arabic textual data utilizing deep learning (DL), natural language processing (NLP), machine learning (ML), and BERT transformers techniques in light of the disease’s high prevalence. …”
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Sentiment works in small-cap stocks: Japanese stock’s sentiment with language models by Masahiro Suzuki, Yasushi Ishikawa, Masayuki Teraguchi, Hiroki Sakaji

“…Language models such as BERT and ChatGPT are advancing the application of natural language processing (NLP) to financial fields. We construct multiple sentiment calculation methods using sentiment dictionaries, models trained on existing sentiment datasets, ChatGPT, and GPT-4. …”
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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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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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Clinical entity-aware domain adaptation in low resource setting for inflammatory bowel disease by Sumam Francis, Fernando Crema Garcia, Kanimozhi Uma, Willem Mestdagh, Bart De Moor, Marie-Francine Moens

“…Extracting valuable information from unstructured clinical text presents a significant challenge, necessitating automated tools for efficient data mining. Natural language processing (NLP) methods have been pivotal in this endeavor, aiming to extract crucial clinical concepts embedded within free-form text. …”
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Tokenizers for African Languages by Goodwill Erasmo Ndomba, Medard Edmund Mswahili, Young-Seob Jeong

“…Despite incredible development in the field of natural language processing (NLP), there has been a huge gap in the performance of NLP tasks between high-resource languages (HRLs) and low-resource languages (LRLs). …”
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