AI‐driven simplification of surgical reports in gynecologic oncology: A potential tool for patient education by Maximilian Riedel, Bastian Meyer, Raphael Kfuri Rubens, Caroline Riedel, Niklas Amann, Marion Kiechle, Fabian Riedel

“…Abstract Introduction The emergence of large language models heralds a new chapter in natural language processing, with immense potential for improving medical care and especially medical oncology. …”
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Application of the LDA model to identify topics in telemedicine conversations on the X social network by Mario Sierra Martín, Fang-Wei Chen, Pilar Alarcón Urbistondo

“…Methods Natural Language Processing (NLP) and Machine Learning techniques, specifically the Latent Dirichlet Allocation (LDA) model, were used to analyse 156,633 comments extracted from “X” related to telemedicine topics. …”
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Assessment on Prevalence and Risk Factors of Dyslexia among Primary School Students by R Rajesh, Honeymol Sunney

“…Background: Dyslexia is a specific learning disability that affects reading skills and language processing. Children with dyslexia have difficulty in reading, writing, spelling, grammar or in speaking. …”
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The processing of familiar English L2 phrasal verbs in neutral and biased sentence contexts by Jianyao Yu, Jianyao Yu, Siya Wang, Siya Wang, Ping Zhang, Tai’an Chen, Tai’an Chen

“…In conclusion, this study enhances our understanding the mechanisms underlying L2 PV processing dynamics and provides actionable insights for language acquisition strategies, thus contributing valuable knowledge to the field of second language processing and learning.…”
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Transformers: A Security Perspective by Banafsheh Saber Latibari, Najmeh Nazari, Muhtasim Alam Chowdhury, Kevin Immanuel Gubbi, Chongzhou Fang, Sujan Ghimire, Elahe Hosseini, Hossein Sayadi, Houman Homayoun, Soheil Salehi, Avesta Sasan

“…The Transformers architecture has recently emerged as a revolutionary paradigm in the field of deep learning, particularly excelling in Natural Language Processing (NLP) and Computer Vision (CV) applications. …”
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Multi-Modal Emotion Detection and Sentiment Analysis by Shoaib Sikunder Malik, Muhammad Ilyas, Yasin Ul Haq, Rabia Sana, Muhamamd Saad Razzaq, Fahad Maqbool, Muhammad Salman Pathan

“…The sentiment classification of videos is emerging as a vital area of research in Natural Language Processing (NLP) and is challenging due to complexity of emotions and temporal aspects of modalities. …”
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The Application of Artificial Intelligence in Medical Diagnostics: Implications for Sports Medicine by Michał Bolek, Dominika Musialska, Aleksandra Kędzia, Bartosz Jagieła, Monika Fidyk, Magda Minkiewicz, Maciej Dyda

“…With 25 years of development, AI technologies, including machine learning, deep learning, natural language processing, and computer vision, are making significant strides in interpreting medical data and supporting clinical decision-making. …”
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Annotated data for semantic role labeling of crisis events in Indonesian TweetsMendeley Data by Amelia Devi Putri Ariyanto, Diana Purwitasari, Bilqis Amaliah, Chastine Fatichah, Muhammad Ghifari Taqiuddin, Haikal

“…By providing this dataset, the research opens up new opportunities for developing Natural Language Processing (NLP) in Indonesian, especially in crisis event analysis.…”
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Time-Series Large Language Models: A Systematic Review of State-of-the-Art by Shamsu Abdullahi, Kamaluddeen Usman Danyaro, Abubakar Zakari, Izzatdin Abdul Aziz, Noor Amila Wan Abdullah Zawawi, Shamsuddeen Adamu

“…Large Language Models (LLMs) have transformed Natural Language Processing (NLP) and Software Engineering by fostering innovation, streamlining processes, and enabling data-driven decision-making. …”
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Enhancing Hajj and Umrah Services Through Predictive Social Media Classification by Samia Allaoua Chelloug, Mohammed Saleh Ali Muthanna, Faisal Jamil, Mehdhar S. A. M. Al-Gaashani, Soha Alhelaly, Ahmed Aziz, Ammar Muthanna

“…Leveraging real-time data from various microblogging platforms Twitter, blogging websites, Facebook, and Instagram, our model classifies individual posts using natural language processing techniques. The classification is based on relevant attributes such as service-level scores. …”
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Subvalvular techniques enhanced with endoscopic robotic mitral valve repairCentral MessagePerspective by Michael Dorsey, MD, Les James, MD, MPH, Shashwat Shrivastava, MD, Didier Loulmet, MD, Eugene A. Grossi, MD

“…Methods: All robotic mitral procedures performed by a 2-surgeon team in a quaternary care medical center from July 2011 to May 2022 were reviewed. Natural language-processing techniques were used to analyze operative reports for subvalvular repair techniques. …”
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Justifying the selection of a neural network linguistic classifier by Олеся Барковська, Ксенія Воропаєва, Олександр Руських

“… The subject matter of this article revolves around the exploration of neural network architectures to enhance the accuracy of text classification, particularly within the realm of natural language processing. The significance of text classification has grown notably in recent years due to its pivotal role in various applications like sentiment analysis, content filtering, and information categorization. …”
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Knowledge Model and Construction of Soybean Breeding by Zhihao GUAN, Zhiyi SHAN, Tian LI, Ruixue ZHAO

“…The limitation of this study is that the ontology was constructed manually and no automated natural language processing method was used. In addition, in the subsequent use of soybean breeding knowledge model, it is necessary to keep up with the frontier of development in soybean breeding, expand new concept types, add new concept names and relationship names in time according to the knowledge description needs of field scientists, and regularly maintain and expand soybean breeding knowledge model.…”
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Predicting sepsis treatment decisions in the paediatric emergency department using machine learning: the AiSEPTRON study by Damian Roland, Ewan Carr, Akash Deep, Sylvester Gomes, Harpreet Dhanoa, Phil Assheton

“…XGBoost, the best-performing machine learning model, integrated these predictors with triage note information extracted via Natural Language Processing.Main outcomes (1) Administration of antibiotics; (2) critical care: antibiotics with fluid resuscitation above 20 mL/kg or non-elective mechanical ventilation; (3) serious infection: hospital admission for antibiotics >48 hours.Model performance was evaluated using area under the receiver operating characteristic curve (AUC), likelihood ratios and positive and negative predictive values.Results Triage model: predicted antibiotics at triage (n=35 795; 3.2% with outcome) with an AUC of 0.80 (95% CI 0.76 to 0.84).Antibiotic model: predicted antibiotics post-blood tests (n=4700; 24.2%) with an AUC of 0.78 (95% CI 0.73 to 0.81).Critical care model: predicted critical care (n=4700; 3.3%) with an AUC of 0.78 (95% CI 0.72 to 084).Serious infection model: predicted serious infection (n=4700; 9.4%) with an AUC of 0.76 (95% CI 0.71 to 0.81).Key predictors included triage category, temperature, capillary refill time and C reactive protein.Conclusion Machine learning models demonstrated good accuracy in predicting antibiotic use following triage and moderate accuracy for critical care and serious infection. …”
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Exploring the relationship between features calculated from contextual embeddings and EEG band power during sentence reading in Chinese by Yao Wang, Yao Wang, Yao Wang, Tiantian Xue, Tiantian Xue, Tiantian Xue, Xingyu Yang, Xingyu Yang, Xingyu Yang

“…This alignment supports the theoretical framework proposing vector-based neural coding for natural language processing in the brain, where linguistic units may be represented as context-sensitive vectors analogous to LLM-derived embeddings. …”
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The intelligent evaluation model of the English humanistic landscape in agricultural industrial parks by the SPEAKING model: From the perspective of fish-vegetable symbiosis in new... by Yiping He, Mingyue Gao, Luyao Wang

“…The proposed model significantly contributes to improving the accuracy and adaptability of language expression in the context of agricultural landscapes, advancing research in intelligent translation and natural language processing.…”
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Taming Mambas for 3D Medical Image Segmentation by Luca Lumetti, Vittorio Pipoli, Kevin Marchesini, Elisa Ficarra, Costantino Grana, Federico Bolelli

“…A recent breakthrough is Mamba, a Recurrent Neural Network (RNN) based on State-Space Models (SSMs), outperforming Transformers in many long-context tasks (million-length sequences) on famous natural language processing and genomic benchmarks while keeping a linear complexity. …”
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Evaluating GPT-4 as an academic support tool for clinicians: a comparative analysis of case records from the literature by B.L. Fabre, M.A.F. Magalhaes Filho, P.N. Aguiar, Jr, F.M. da Costa, B. Gutierres, W.N. William, Jr, A. Del Giglio

“…Background: Artificial intelligence (AI) and natural language processing (NLP) advancements have led to sophisticated tools like GPT-4.0, allowing clinicians to explore its utility as a health care management support tool. …”
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Efficient Method for Robust Backdoor Detection and Removal in Feature Space Using Clean Data by Donik Vrsnak, Marko Subasic, Sven Loncaric

“…These methods target different areas, such as computer vision (CV), natural language processing (NLP), and thus utilize different assumptions about the nature of the input data and the type of backdoor trigger used in the attack. …”
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Graph-to-Text Generation with Bidirectional Dual Cross-Attention and Concatenation by Elias Lemuye Jimale, Wenyu Chen, Mugahed A. Al-antari, Yeong Hyeon Gu, Victor Kwaku Agbesi, Wasif Feroze, Feidu Akmel, Juhar Mohammed Assefa, Ali Shahzad

“…While transformer-based encoders have advanced natural language processing, their reliance on linearized data often obscures the complex interrelationships in graph structures, leading to structural loss. …”
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