Artificial intelligence-driven clinical decision support systems for early detection and precision therapy in oral cancer: a mini review by Manoj Kumar Karuppan Perumal, Remya Rajan Renuka, Suresh Kumar Subbiah, Prabhu Manickam Natarajan

“…In addition, it examines current implementations of AI-CDSS that facilitate early OC detection, precise staging, and personalized treatment planning by processing multimodal patient information through machine learning, computer vision, and natural language processing. These systems effectively interpret clinical results, identify critical disease patterns (including clinical stage, site, tumor dimensions, histopathologic grading, and molecular profiles), and construct comprehensive patient profiles. …”
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In-context learning enables multimodal large language models to classify cancer pathology images by Dyke Ferber, Georg Wölflein, Isabella C. Wiest, Marta Ligero, Srividhya Sainath, Narmin Ghaffari Laleh, Omar S. M. El Nahhas, Gustav Müller-Franzes, Dirk Jäger, Daniel Truhn, Jakob Nikolas Kather

“…However, this process is computationally and technically demanding. In language processing, in-context learning provides an alternative, where models learn from within prompts, bypassing the need for parameter updates. …”
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Opioid Crisis Detection in Social Media Discourse Using Deep Learning Approach by Muhammad Ahmad, Grigori Sidorov, Maaz Amjad, Iqra Ameer, Ildar Batyrshin

“…This study investigates the efficacy of an automated tool leveraging natural language processing and transformer model, such as RoBERTa, to analyze patterns of substance use. …”
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Digital insights: Analyzing the reproductive intentions and influencing factors among urban women in China through online platforms. by Jing Xiang, Xuan Sun

“…<h4>Methods</h4>This study employed natural language processing (NLP), TF-IDF-based semantic analysis, and multinomial logistic regression to analyze user-generated content from Douyin, Xiaohongshu, and Kuaishou. …”
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Position-context additive transformer-based model for classifying text data on social media by M. M. Abd-Elaziz, Nora El-Rashidy, Ahmed Abou Elfetouh, Hazem M. El-Bakry

“…Abstract In recent years, the continuous increase in the growth of text data on social media has been a major reason to rely on the pre-training method to develop new text classification models specially transformer-based models that have proven worthwhile in most natural language processing tasks. This paper introduces a new Position-Context Additive transformer-based model (PCA model) that consists of two-phases to increase the accuracy of text classification tasks on social media. …”
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Research on digital matching methods integrating user intent and patent technology characteristics by Jianwei Yang, Yi Wang, Bonan Zang, Min Peng, George Torrens

“…Second, based on the characteristics of patent texts, an N-V-N structure (noun-verb-noun) is constructed, and Natural Language Processing (NLP) technology is used to extract patent technical features. …”
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Physics instructors’ acceptance and implementation of generative AI by Pornrat Wattanakasiwich, Kreetha Kaewkhong, Duanghatai Katwibun

“…We found instructors distributed across different adoption stages, with key barriers including insufficient technical knowledge (51.75% of nonusers) and language processing limitations (50.5% of users). Hedonic motivation (β=0.498) was found to have a substantially stronger influence on adoption than performance expectancy (β=0.121), with an effect size approximately 4 times greater. …”
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Analyzing social psychological impact on emotional expression through peer communication using crayfish optimization algorithm with deep learning model by Umkalthoom Alzubaidi

“…Emotional recognition in the text document is primarily a content-based classification problem containing ideas from natural language processing (NLP). NLP methods enhance the performance of learning-based models by combining the syntactic and semantic features of the text. …”
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Content analysis of multi-annual time series of flood-related Twitter (X) data by N. Veigel, N. Veigel, N. Veigel, H. Kreibich, J. A. de Bruijn, J. A. de Bruijn, J. C. J. H. Aerts, J. C. J. H. Aerts, A. Cominola, A. Cominola

“…In this study, we present a natural language processing analytic framework to extract and categorize information from 43 287 textual Twitter (X) posts in German since 2014. …”
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Development of a Knowledge Graph-Based Model for Recommending MOOCs to Supplement University Educational Programs in Line With Employer Requirements by Valiya Ramazanova, Madina Sambetbayeva, Sandugash Serikbayeva, Zhanna Sadirmekova, Aigerim Yerimbetova

“…The use of natural language processing techniques allows not only capturing explicit keyword matches, but also recognizing deep semantic connections, which is an integral part of accurate matching in educational and professional domains. …”
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Research on the Automatic Multi-Label Classification of Flight Instructor Comments Based on Transformer and Graph Neural Networks by Zejian Liang, Yunxiang Zhao, Mengyuan Wang, Hong Huang, Haiwen Xu

“…This approach enhances the consistency and efficiency of flight training assessments and provides new insights into integrating natural language processing and graph neural networks, demonstrating broad application prospects.…”
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Temporal Dynamics in Short Text Classification: Enhancing Semantic Understanding Through Time-Aware Model by Khaled Abdalgader, Atheer A. Matroud, Ghaleb Al-Doboni

“…This work advances natural language processing by offering a comprehensive time-aware classification framework, addressing the challenges of temporal dynamics in language semantics.…”
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Harnessing digital health data for suicide prevention and care: A rapid review by Laura Bennett-Poynter, Sridevi Kundurthi, Reena Besa, Dan W. Joyce, Andrey Kormilitzin, Nelson Shen, James Sunwoo, Patrycja Szkudlarek, Lydia Sequiera, Laura Sikstrom

“…Conclusions Recommendations for future research and practice include prioritizing engagement with knowledge users, establishing robust data governance frameworks aligned with clinical guidelines, and leveraging advanced analytics, such as natural language processing, to improve the quality of health equity data.…”
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Bridging or Burning? Digital Sustainability and PY Students’ Intentions to Adopt AI-NLP in Educational Contexts by Mostafa Aboulnour Salem

“…The current study examines the determinants influencing preparatory year (PY) students’ intentions to adopt AI-powered natural language processing (NLP) models, such as Copilot, ChatGPT, and Gemini, and how these intentions shape their conceptions of digital sustainability. …”
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Retrospective study of onychomycosis patients treated with ciclopirox 8% HPCH and oral antifungals applying artificial intelligence to electronic health records by Gastón Roustan, José Luis López Estébaranz, Pablo De La Cueva, Savana Research Group, Francesca Pajuelo, María Luisa Tamarit, Aida Valmaseda, Jordi Galván

“…Data were extracted and analyzed using the EHRead® technology based on natural language processing and machine learning and using SNOMED CT terminology. …”
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Coronavirus research topics, tracking twenty years of research by Amir Aryani, Jingbo Wang, Luis Salvador-Carulla, Jihoon Woo, Cathy P. W. Cheung, Zhuochen Wu, Hui Yin, Junhua Xiao, Elisabeth A. Lambert, Jason Howitt, Jean M. Davidson, Serene Yoong, John B. Dixon, Rachel E. Climie, Jose A. Salinas-Perez, Nasser Bagheri, Celine Santiago, Joanne Williams, Nilmini Wickramasinghe, Leo Ng, Clara C. Zwack, Gavin W. Lambert

“…To explore research trends and innovations in this space, we developed a pipeline using natural language processing techniques. This pipeline systematically catalogues and synthesises the vast array of research articles, leading to the creation of a dataset with more than eight hundred thousand articles from July 2002 to May 2024. …”
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Unraveling consistently altered brain activations of language deficits in schizophrenia: evidence from ALE meta-analysis by Yuwen He, Ya Hou, Yuan Zhou, Ruolei Gu, Fei Gao, Zhen Yuan

“…Methods We systematically reviewed fMRI publications on language processing in schizophrenia and summarized the evidence quantitatively with activation likelihood estimation algorithms following PRISMA guidelines. …”
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Online Eye Tracking for Aphasia: A Feasibility Study Comparing Web and Lab Tracking and Implications for Clinical Use by Willem S. vanBoxtel, Michael Linge, Rylee Manning, Lily N. Haven, Jiyeon Lee

“…Discussion & Conclusions Web‐based eye tracking is feasible to study impaired language processing in aphasia and is sensitive enough to detect most group differences between controls and patients. …”
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Evaluation of large language models as a diagnostic tool for medical learners and clinicians using advanced prompting techniques. by Karolina Gaebe, Benjamin van der Woerd

“…<h4>Background</h4>Large language models (LLMs) have demonstrated capabilities in natural language processing and critical reasoning. Studies investigating their potential use as healthcare diagnostic tools have largely relied on proprietary models like ChatGPT and have not explored the application of advanced prompt engineering techniques. …”
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Sztuczna inteligencja w służbie tworzenia treści na przykładzie portalu internetowego skierowanego do polskiej społeczności w Hiszpanii by Paweł Kijko

“…Do tworzenia treści na wskazanym portalu posłużono się narzędziami z zakresu NLP (natural language processing), które pomagały w tworzeniu artykułów na stronie. …”
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