Toward AI-Augmented Formal Verification: A Preliminary Investigation of ENGRU and Its Challenges by Chanon Dechsupa, Teerapong Panboonyuen, Wiwat Vatanawood, Praisan Padungweang, Chakchai So-In

“…Recurrent neural networks (RNNs) and language models are deeply intertwined, as RNNS provide the foundational architecture that enables language models to process sequential data, capture contextual dependencies, and improve natural language processing tasks. Both RNNs and state-space graphs help evaluate discrete-time systems within this formal framework. …”
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Event Type and Relationship Extraction Based on Dependent Syntactic Semantic Augmented Graph Networks by Min Zuo, Zexi Song, Qingchuan Zhang, Yueheng Liu, Di Wu, Yuanyuan Cai

“…In natural language processing, tasks like trigger word extraction, event type recognition, and event relation extraction are essential. …”
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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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Improving Performance of Automatic Keyword Extraction (AKE) Methods Using PoS Tagging and Enhanced Semantic-Awareness by Enes Altuncu, Jason R. C. Nurse, Yang Xu, Jie Guo, Shujun Li

“…It has various applications in information retrieval (IR) and natural language processing (NLP), including text summarisation, topic analysis and document indexing. …”
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Transformers and large language models are efficient feature extractors for electronic health record studies by Kevin Yuan, Chang Ho Yoon, Qingze Gu, Henry Munby, A. Sarah Walker, Tingting Zhu, David W. Eyre

“…Methods We evaluated the efficacy of feature extraction using modern natural language processing methods (NLP) and large language models (LLMs) on 938,150 hospital antibiotic prescriptions from Oxfordshire, UK. …”
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From manual clinical criteria to machine learning algorithms: Comparing outcome endpoints derived from diverse electronic health record data modalities. by Shreya Chappidi, Mason J Belue, Stephanie A Harmon, Sarisha Jagasia, Ying Zhuge, Erdal Tasci, Baris Turkbey, Jatinder Singh, Kevin Camphausen, Andra V Krauze

“…Three methods were developed to derive clinical PFS: 1) frequency analysis of corticosteroid prescriptions, 2) natural language processing (NLP) of reports, and 3) computer vision (CV) volumetric analysis of imaging. …”
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Machine Learning-Powered Smart Healthcare Systems in the Era of Big Data: Applications, Diagnostic Insights, Challenges, and Ethical Implications by Sita Rani, Raman Kumar, B. S. Panda, Rajender Kumar, Nafaa Farhan Muften, Mayada Ahmed Abass, Jasmina Lozanović

“…Applications in real-world settings, such as disease prediction, medical imaging, drug discovery, and remote monitoring, illustrate how ML methods, such as deep learning (DL) and natural language processing (NLP), enhance clinical decision-making. …”
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Features of Recruitment: Intelligent Text Analysis of Resume and Vacancies by Irina L. Sizova

“…An original methodology for analyzing labor market big data was developed, based on 5,347,805 texts of resumes and job postings collected from three largest Russian platforms for the period 2019–2024. Natural Language Processing (NLP) algorithms, including topic modeling and clustering, were used to process the data, enabling the creation of two hierarchical taxonomies: 55 competency parameters and 423 groups of job responsibilities. …”
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Inflectional Changes of Double Marked Form: Evidence from a Corpus Study of English Verbal System by Basima Othman Mahmood

“…Morphological aspects of language processing. (pp. 55–76). Hillsdale, NJ: Lawrence Erlbaum Associates. …”
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Dresses and ties: the effect of grammatical gender and stereotypical semantic bias in three Spanish-speaking communities by Gabriela Mariel Zunino, Miriam Aguilar, Noelia Ayelén Stetie, Camila Martínez Rebolledo, José Antonio Hinojosa

“…Stereotype construction is a complex process, with multiple relations to language processing, that combines collective sociocultural factors with individual cognitive elements. …”
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MoveMentor—examining the effectiveness of a machine learning and app-based digital assistant to increase physical activity in adults: protocol for a randomised controlled trial by Corneel Vandelanotte, Stewart Trost, Danya Hodgetts, Tasadduq Imam, MD Mamunur Rashid, Quyen G. To, Carol Maher

“…Intervention participants will gain access to an app-based physical activity digital assistant that can learn and adapt in real-time to achieve high levels of personalisation and user engagement by virtue of applying a range of machine learning techniques (i.e. reinforcement learning, natural language processing and large language models). The digital assistant will interact with participants in 3 main ways: (1) educational conversations about physical activity; (2) just-in-time personalised in-app notifications (‘nudges’), cues to action encouraging physical activity and (3) chat-based questions and answers about physical activity. …”
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Psychosocial considerations in pediatric heart transplantation: Initial validation of the Pediatric Psychosocial Assessment Tool at a single center by Michael O. Killian, PhD, MSW, Sonnie E. Mayewski, MSW, Schyler E. Brumm, MSW, Zhe He, PhD, Dipankar Gupta, MBBS, DCH, MD

“…Future directions include expanding implementation to other centers and integrating the PPAT into digital platforms using artificial intelligence and natural language processing to enhance efficiency, consistency, and patient-centered care.…”
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Truth be told: a multimodal ensemble approach for enhanced fake news detection in textual and visual media by Rami Mohawesh, Islam Obaidat, Ahmed Abdallah AlQarni, Ali Abdulaziz Aljubailan, Moy’awiah A. Al-Shannaq, Haythem Bany Salameh, Ali Al-Yousef, Ahmad A. Saifan, Suboh M. Alkhushayni, Sumbal Maqsood

“…Abstract Fake news detection (FND) has emerged as a pivotal domain within the natural language processing field. The primary goal of FND is to discern and evaluate the veracity of pivotal claims in news articles, thereby determining the credibility of the presented news. …”
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Extracting Pulmonary Embolism Diagnoses From Radiology Impressions Using GPT-4o: Large Language Model Evaluation Study by Mohammed Mahyoub, Kacie Dougherty, Ajit Shukla

“…Advances in natural language processing, especially transformer models like GPT-4o, offer promising tools to improve diagnostic accuracy and workflow efficiency in clinical settings. …”
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Social Media Network Analysis of Academic Urologists’ Interaction Within Twitter Microblogging Environment by Spencer H. Bell, Clara Sun, Emma Helstrom, Justin M. Dubin, Ilaha Isali, Kirtishri Mishra, Andrew Gianakopoulos, Seyed Behzad Jazayeri, Mohit Sindhani, Lee Ponsky, Alexander Kutikov, Casey Seideman, Andres Correa, Diana Magee, Laura Bukavina

“…Analyzed tweets were further evaluated using natural language processing for sentiment association, mentions, and quote tweeted and retweeted. …”
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The impact of artificial intelligence on medical diagnostics: A letter to the editor by Sahar Imtiaz, Sheikh Abdul Qadir Jillani

“… Madam, Artificial intelligence (AI) describes the generation of intelligent machines that are capable of carrying out activities that usually call for human intellect. (1) It involves creating algorithms and models that enable computers to learn from and analyze vast amounts of data, recognize patterns, make decisions, and even engage in natural language processing.  (2) AI has become increasingly important in various fields due to its potential to automate complex processes, enhance efficiency, and drive innovation. …”
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Patient and nodule characteristics associated with adherence to lung cancer screening in a large integrated healthcare system by Shuang Yang, Muxuan Liang, Hiren J. Mehta, Ramzi G. Salloum, Dejana Braithwaite, Yonghui Wu, Jessica Islam, Xuhong Zhang, Ya-Chen Tina Shih, Jinhai Huo, Jiang Bian, Yi Guo

“…Using 2014–2021 electronic health record data from a large integrated health system, we analyzed adherence to Lung Imaging Reporting and Data System (Lung-RADS) follow-up recommendations, considering socio-demographic, clinical factors, and natural language processing-extracted nodule characteristics. Multivariable logistic regression models assessed the impact of these factors on adherence to follow-up LDCT. …”
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Technological Solutions to Improve Inpatient Handover in the Era of Artificial Intelligence: Scoping Review by Louis Agha-Mir-Salim, Isabelle Rose Alberto, Nicole Rose Alberto, Leo Anthony Celi, Pia Gabrielle Alfonso, Rachel Hicklen, Katelyn Legaspi, Rajiv Hans Menghrajani, Faye Yu Ng, Patricia Therese Pile, Christopher M Sauer

“…Analysis revealed a predominance of low-complexity technologies, such as electronic checklists, with limited exploration of advanced solutions like natural language processing. Most studies were in the pilot stage (33/53, 62%), while some described documented implementations (11/53, 21%). …”
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Enhancing personalized learning: AI-driven identification of learning styles and content modification strategies by Md. Kabin Hasan Kanchon, Mahir Sadman, Kaniz Fatema Nabila, Ramisa Tarannum, Riasat Khan

“…Next, the text content of the electronic documents is modified by employing different natural language processing (NLP) techniques, including named entity recognition of spaCy, knowledge graph, generative pre-trained transformer 3 (GPT-3), and text-to-text transfer transformer (T5) model, to accommodate diverse learning styles. …”
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Leveraging Artificial Intelligence and Data Science for Integration of Social Determinants of Health in Emergency Medicine: Scoping Review by Ethan E Abbott, Donald Apakama, Lynne D Richardson, Lili Chan, Girish N Nadkarni

“…Machine learning (ML) techniques were used in 23 of 26 studies, with natural language processing (NLP) being the most commonly used approach (n=11). …”
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