Biomedical named entity recognition using improved green anaconda-assisted Bi-GRU-based hierarchical ResNet model by Ram Chandra Bhushan, Rakesh Kumar Donthi, Yojitha Chilukuri, Ulligaddala Srinivasarao, Polisetty Swetha

“…Results This research has proposed a novel model to address the challenges in natural language processing. The Improved Green anaconda-assisted Bi-GRU based Hierarchical ResNet BNER model (IGa-BiHR BNERM) is the model. …”
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Impact of Off-Time on Quality of Life in Parkinson’s Patients and Their Caregivers: Insights from Social Media by Philippe Damier, Emily J. Henderson, Jesús Romero-Imbroda, Laura Galimam, Nick Kronfeld, Tobias Warnecke

“…A random sample of these posts was then analyzed using natural language processing (NLP), and quantitative, qualitative,in-depth contextual analysis was also performed. …”
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Revolutionizing Health Care: The Transformative Impact of Large Language Models in Medicine by Kuo Zhang, Xiangbin Meng, Xiangyu Yan, Jiaming Ji, Jingqian Liu, Hua Xu, Heng Zhang, Da Liu, Jingjia Wang, Xuliang Wang, Jun Gao, Yuan-geng-shuo Wang, Chunli Shao, Wenyao Wang, Jiarong Li, Ming-Qi Zheng, Yaodong Yang, Yi-Da Tang

“…These models excel in natural language processing (NLP), enhancing clinical support, diagnosis, treatment, and medical research. …”
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Nonparametric analysis of inter‐individual relations using an attention‐based neural network by Takashi Morita, Aru Toyoda, Seitaro Aisu, Akihisa Kaneko, Naoko Suda‐Hashimoto, Ikuma Adachi, Ikki Matsuda, Hiroki Koda

“…In this study, researchers explored a nonparametric analysis of inter‐individual relations using a neural network with the attention mechanism, which plays a central role in natural language processing. The high interpretability of the attention mechanism and flexibility of the entire neural network allow for automatic detection of inter‐individual relations included in the raw data, without requiring prior knowledge/assumptions about what modes/types of relations are included in the data. …”
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Sentiment analysis of the Hamas-Israel war on YouTube comments using deep learning by Ashagrew Liyih, Shegaw Anagaw, Minichel Yibeyin, Yitayal Tehone

“…Then, textual comments were preprocessed using natural language processing (NLP) techniques, and features were extracted using Word2vec, FastText, and GloVe. …”
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Performance assessment of ChatGPT 4, ChatGPT 3.5, Gemini Advanced Pro 1.5 and Bard 2.0 to problem solving in pathology in French language by Georges Tarris, Laurent Martin

“…Digital teaching diversifies the ways of knowledge assessment, as natural language processing offers the possibility of answering questions posed by students and teachers. …”
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CODE-ACCORD: A Corpus of building regulatory data for rule generation towards automatic compliance checking by Hansi Hettiarachchi, Amna Dridi, Mohamed Medhat Gaber, Pouyan Parsafard, Nicoleta Bocaneala, Katja Breitenfelder, Gonçal Costa, Maria Hedblom, Mihaela Juganaru-Mathieu, Thamer Mecharnia, Sumee Park, He Tan, Abdel-Rahman H. Tawil, Edlira Vakaj

“…CODE-ACCORD supports a range of ML and Natural Language Processing (NLP) tasks, including text classification, entity recognition, and relation extraction. …”
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A Hybrid Transformer Architecture for Multiclass Mental Illness Prediction Using Social Media Text by Adnan Karamat, Muhammad Imran, Muhammad Usman Yaseen, Rasool Bukhsh, Sheraz Aslam, Nouman Ashraf

“…Mental illness prediction through text involves employing natural language processing (NLP) techniques and deep learning algorithms to analyze textual data for the identification of mental disorders. …”
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Img2Side: A Transfer Learning Based Model for Predicting Drug Side Effects Using 2D Chemical Structural Images by Muhammad Asad Arshed, Muhammad Ibrahim, Shahzad Mumtaz, Tenvir Ali, Gyu Sang Choi

“…Previously, proposed studies for the prediction/prevention of DSEs utilized the features of 1D drug chemical structures or Natural Language Processing (NLP). Both these techniques required a complex transformation process. …”
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Hierarchical graph-based integration network for propaganda detection in textual news articles on social media by Pir Noman Ahmad, Jiequn Guo, Nagwa M. AboElenein, Qazi Mazhar ul Haq, Sadique Ahmad, Abeer D. Algarni, Abdelhamied A. Ateya

“…Existing graph-based models, such as Graph Neural Networks (GNNs), have achieved notable success in Natural Language Processing (NLP). However, utilizing GNN-based models for propaganda detection remains challenging because of the challenges related to mining distinct word interactions and storing nonconsecutive and broad contextual data. …”
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A deep learning analysis for dual healthcare system users and risk of opioid use disorder by Ying Yin, Elizabeth Workman, Phillip Ma, Yan Cheng, Yijun Shao, Joseph L. Goulet, Friedhelm Sandbrink, Cynthia Brandt, Christopher Spevak, Jacob T. Kean, William Becker, Alexander Libin, Nawar Shara, Helen M. Sheriff, Jorie Butler, Rajeev M. Agrawal, Joel Kupersmith, Qing Zeng-Trietler

“…Of the cohort, 146,688(17%) had OUD, determined through Natural Language Processing of clinical notes and ICD-9/10 diagnoses. …”
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Morphologically-analyzed and syntactically-annotated Quran datasetMendeley Data by Majdi Sawalha, Faisal Al-Shargi, Sane Yagi, Abdallah T. AlShdaifat, Bassam Hammo, Mariam Belajeed, Lubna R. Al-Ogaili

“…This paper introduces the Morphologically-Analyzed and Syntactically-Annotated Quran (MASAQ) dataset, a comprehensive resource designed to address the scarcity of annotated Quranic Arabic corpora and facilitate the development of advanced Natural Language Processing (NLP) models. The Quran, being a cornerstone of classical Arabic, presents unique challenges for NLP due to its sacred nature and complex linguistic features. …”
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The Recent Technologies to Curb the Second-Wave of COVID-19 Pandemic by M. Poongodi, Mohit Malviya, Mounir Hamdi, Hafiz Tayyab Rauf, Seifedine Kadry, Orawit Thinnukool

“…Large data sets need to be advanced so that extensive models related to deep analysis can be used to combat Coronavirus infection, which can be done by applying Artificial intelligence techniques such as Natural Language Processing (NLP), Machine Learning (ML), and Computer vision to varying processing files. …”
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Evaluating machine learning models for supernova gravitational wave signal classification by Y Sultan Abylkairov, Matthew C Edwards, Daniil Orel, Ayan Mitra, Bekdaulet Shukirgaliyev, Ernazar Abdikamalov

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Large language models for accurate disease detection in electronic health records: the examples of crystal arthropathies by Kim Lauper, Denis Mongin, Nils Bürgisser, Samia Mehouachi, Clement P. Buclin, Delphine S. Courvoisier, Etienne Chalot

“…The study compares the performance of the LLM-based framework with traditional natural language processing techniques and tests its dependence on the parameter used.Methods The framework was developed using a training and testing set of 700 paragraphs assessing ‘gout’ from a random selection of EHR documents from a tertiary university hospital in Geneva, Switzerland. …”
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COMMUNICATIVE TYPE “MUNICIPAL EMPLOYEE” IN THE MEDIA SPACE: DEVELOPMENT OF AN AUTOMATIC INFORMATION AND ANALYTICAL ASSESSMENT SYSTEM by Irina S. Karabulatova, Konstantin V. Vorontsov, Daniil A. Okolyshev, Ludan Zhang

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Arsitektur Sistem Percakapan Otomatis Berbahasa Indonesia dengan Normalisasi Bahasa Informal Menjadi Baku by Muhammad Fathur Rahman Khairul, Rizal Setya Perdana

“…This is an issue from a natural language processing (NLP) perspective. NLP generally only works with formal language and is unable to interpret the meaning of informal sentences. …”
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UEF-HOCUrdu: Unified Embeddings Ensemble Framework for Hate and Offensive Text Classification in Urdu by Kifayat Ullah, Muhammad Aslam, Muhammad Usman Ghani Khan, Faten S. Alamri, Amjad Rehman Khan

“…This study sought to create a model that not only achieves a high classification accuracy but also overcome key challenges inherent in natural language processing, namely, high dimensionality, sparsity, overfitting, OOV words and dialectal variations. …”
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The Impact of Linguistic Signals on Cognitive Change in Support Seekers in Online Mental Health Communities: Text Analysis and Empirical Study by Min Li, Dongxiao Gu, Rui Li, Yadi Gu, Hu Liu, Kaixiang Su, Xiaoyu Wang, Gongrang Zhang

“…Through text mining and natural language processing (NLP) technology, we identified linguistic features in online text and conducted an empirical analysis using 12,868 online mental health support reply data items from Zhihu to verify the effectiveness of those features. …”
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A systematic review of Machine Learning and Deep Learning approaches in Mexico: challenges and opportunities by José Luis Uc Castillo, Ana Elizabeth Marín Celestino, Diego Armando Martínez Cruz, José Tuxpan Vargas, José Alfredo Ramos Leal, Janete Morán Ramírez

“…These models are recognized as powerful tools in many fields due to their capability to carry out several tasks such as forecasting, image classification, recognition, natural language processing, machine translation, etc. This review article aimed to provide comprehensive information on the Machine Learning and Deep Learning algorithms applied in Mexico. …”
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