Apolipoprotein E genotyping variations and their influence on cognitive outcome among idiopathic generalized epileptic patients by Nancy El-Salhy, Noura R. Eissa, Salma Ragab, Gamil M. Abd-Allah, Sara M. Sayed

“…Yet, there was a significant increase in Addenbrooke, memory, fluency, and language processing in ε3/ε3 genotype compared to ε3/ε4 genotype, (P=0.000, 0.007, 0.016, and 0.000, respectively). …”
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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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Text leads, images and videos follow: the impact of processing paths and input modalities on metaphorical competence in Chinese foreign language learners by Siyun Li, Yang Zhao

“…IntroductionMetaphorical competence is crucial in the accurate and authentic use of a second language. Processing paths (rational processing verses contextual guessing) and input modalities (unimodal verses multimodal) are major factors that may influence learners' metaphorical acquisition. …”
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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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Learning Automata Based Incremental Learning Method for Deep Neural Networks by Haonan Guo, Shilin Wang, Jianxun Fan, Shenghong Li

“…Deep learning methods have got fantastic performance on lots of large-scale datasets for machine learning tasks, such as visual recognition and neural language processing. Most of the progress on deep learning in recent years lied on supervised learning, for which the whole dataset with respect to a specific task should be well-prepared before training. …”
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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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EXPLORING AUTOMATED SUMMARIZATION: FROM EXTRACTION TO ABSTRACTION by Svetlana G. Sorokina

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DeepSeek vs. ChatGPT: Comparative Efficacy in Reasoning for Adults’ Second Language Acquisition Analysis by Mohammad Mahyoob Albuhairy, Jeehaan Algaraady

“…The advent of new generation language models has revolutionized the field of natural language processing (NLP) due to their exceptional understanding and human language generation capabilities. …”
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Brain-model neural similarity reveals abstractive summarization performance by Zhejun Zhang, Shaoting Guo, Wenqing Zhou, Yingying Luo, Yingqi Zhu, Lin Zhang, Lei Li

“…These findings deepen our understanding of the cognitive mechanisms underlying language representations in DLMs and their neural correlates, potentially providing insights for optimizing and improving language models by aligning them with the human brain’s language-processing mechanisms.…”
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