Advanced Neural Model for Spanish Spell-Checking by Eduard Gilberto Puerto Cuadros

“…Context: Correcting spelling errors in written content, particularly in Spanish texts, remains a critical challenge in natural language processing (NLP) due to the complexity of word structures and the inefficiency of existing methods when applied to large datasets. …”
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Dynamic in-context learning with conversational models for data extraction and materials property prediction by Chinedu E. Ekuma

“…The advent of natural language processing and large language models (LLMs) has revolutionized the extraction of data from unstructured scholarly papers. …”
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The necessity of artificial intelligence in the nursing curriculum by Ali Pourhabib, Zahra Fotoukian, Amir Rezaie, Fatemeh Shirinkam-choori

“…The curriculum could cover topics such as machine learning, natural language processing, pattern recognition, data mining, and practical applications of AI in nursing, including disease diagnosis, patient condition prediction, and patient-centered care solutions. ...…”
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Applications of artificial intelligence in hospital quality management: a review of digital strategies in healthcare settings by Rosa Elgiba García-García

“…The most widely used technologies include machine learning, deep neural networks, expert systems, and natural language processing. The results show measurable improvements in operational efficiency, diagnostic accuracy, patient safety, and strategic hospital planning. …”
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A study of pipeline parallelism in deep neural networks by Gabriel Núñez, Hairol Romero-Sandí, Elvis Rojas, Esteban Meneses

“…The appearance of chats based on artificial intelligence or natural language processing has generated the creation of increasingly large and sophisticated neural network models, which are the basis of current developments in artificial intelligence. …”
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AI in humanitarian healthcare: a game changer for crisis response by Diala Haykal, Mohamad Goldust, Hugues Cartier, Patrick Treacy

“…Results indicate that AI enhances disaster prediction, disease surveillance, resource allocation, and mental health support through tools such as machine learning, natural language processing, robotics, and blockchain. Prominent applications include AI-powered early warning systems, chatbots for displaced populations, telemedicine platforms, and automated supply chain logistics. …”
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Impartial competitive learning in multi-layered neural networks by Ryotaro Kamimura

“…The intuitive conclusion, stressed in the specific science, could not be extracted by the conventional natural language processing methods, because they can deal only with word frequency. …”
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Deep learning-based multimodal trajectory prediction methods for autonomous driving: state of the art and perspectives by Jun HUANG, Yonglin TIAN, Xingyuan DAI, Xiao WANG, Zhixing PING

“…Although deep learning methods have achieved better results than traditional trajectory prediction algorithms, there are still problems such as information loss, interaction and uncertainty difficulties in modelling, and lack of interpretability of predictions when implementing multimodal high-precision prediction for autonomous vehicles in heterogeneous, highly dynamic and complex changing environments.The newly developed Transformer's long-range modelling capability and parallel computing ability make it a great success not only in the field of natural language processing, but also in solving the above problems when extended to the task of multimodal trajectory prediction for autonomous driving.Based on this, the aim of this paper is to provide a comprehensive summary and review of past deep neural network-based approaches, in particular the Transformer-based approach.The advantages of Transformer over traditional sequential network, graphical neural network and generative model were also analyzed and classified in relation to existing challenges, simultaneously.Transformer models can be better applied to multimodal trajectory prediction tasks, and that such models have better generalisation and interpretability.Finally, the future directions of multimodal trajectory prediction were presented.…”
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Smart Aging: Harnessing Artificial Intelligence to Enhance Elderly Health Care and Independence by Rahul Garg

“…Future directions in this field include advancements in natural language processing, multi-modal data integration, and the development of explainable AI systems. …”
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Psychosocial dynamics of suicidality and nonsuicidal self-injury: a digital linguistic perspective by Charlotte Entwistle, Katie Hoemann, Sophie J. Nightingale, Ryan L. Boyd

“…We utilised natural language processing techniques to analyse Reddit data (i.e., BPD forum posts) of 992 users with self-identified BPD (combined N posts = 66,786). …”
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An open-source family of large encoder-decoder foundation models for chemistry by Eduardo Soares, Emilio Vital Brazil, Victor Shirasuna, Dmitry Zubarev, Renato Cerqueira, Kristin Schmidt

“…Abstract The use of foundation models has extended from natural language processing to molecular modeling. In this context, large-scale pre-training strategies have been applied to chemical language models to enable representation learning across diverse tasks. …”
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Measuring the Effectiveness of Carbon-Aware AI Training Strategies in Cloud Instances: A Confirmation Study by Roberto Vergallo, Luca Mainetti

“…While such strategies have proved to achieve interesting results on a benchmark of modern models covering Natural Language Processing (NLP) and computer vision applications and a wide range of model sizes (up to 6.1B parameters), it is still unclear whether such results may hold also with different algorithms and in different geographical regions. …”
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ARTIFICIAL INTELLIGENCE AND BIG DATA ANALYSIS IN CRIME PREVENTION AND COMBAT by George-Marius ȚICAL

“…Machine learning algorithms, neural networks, and natural language processing enable the rapid analysis of unstructured data, enhancing the ability to predict and prevent crimes. …”
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Flexible Natural Language-Based Image Data Downlink Prioritization for Nanosatellites by Ezra Fielding, Akitoshi Hanazawa

“…This paper determines whether natural language processing can be used to prioritize remote sensing images on CubeSats with more flexibility compared to existing methods. …”
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Evaluating ChatGPT-4's Performance in Identifying Radiological Anatomy in FRCR Part 1 Examination Questions by Pradosh Kumar Sarangi, Suvrankar Datta, Braja Behari Panda, Swaha Panda, Himel Mondal

“…Recent advancements in artificial intelligence (AI) and natural language processing (NLP) have raised interest in the potential of AI models to support radiologists, although robust research on AI performance in this field is still emerging.…”
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Identifying the Origin of Cyber Attacks Using Machine Learning and Network Traffic Analysis by Du Tianqing

“…In this paper, PCAP refers to Packet Capture, Network Intrusion Detection Systems refers to NIDS, Artificial Intelligence refers to AI, machine learning refers to ML, Computer Vision refers to CV, and Natural Language Processing refers to NLP. While the development of the internet promotes global progress, it also brings various cyber-attacks, such as phishing, junk emails, and keylogging. …”
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Challenges and opportunities with ChatGPT in oral oncology: The journey ahead by Ribwar Arsalan Mohammed, Sirwan Khalid Ahmed

“…ChatGPT's use of natural language processing enables it to analyze complex medical data, aiding in early cancer detection and personalized treatment planning based on evidence-based guidelines. …”
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Current AI Applications and Challenges in Oral Pathology by Zaizhen Xu, Alice Lin, Xiaoyuan Han

“…Artificial intelligence (AI), particularly through machine learning (ML) and deep learning (DL) techniques such as convolutional neural networks (CNNs) and natural language processing (NLP), has shown remarkable promise in image analysis and clinical documentation in oral pathology. …”
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Il Sistema Traduco nel Progetto Traduzione del Talmud Babilonese by Andrea Bellandi, Giulia Benotto, Davide Albanesi, Emiliano Giovannetti

“…Translators, revisors, editors, supervisors, and end-users accessing the system are supported throughout the translation process, from interpreting the original text to the editorial phase for the printing of translations, through the use of computer-assisted translation technologies, semantic annotation of the text, enrichment of translations with explanatory information, export of translations in XML and TEI, and integration of techniques for natural language processing. The design and development of Traduco required the adoption of a multidisciplinary approach that combines aspects of software engineering, computational linguistics, knowledge engineering, and digital publishing.…”
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Breaking down barriers to warning technology adoption: usability and usefulness of a messenger app warning bot by Haunschild Jasmin, Henkel Markus, Reuter Christian

“…The derived requirements and design solutions, such as graphically enhanced user interface elements as guardrails for effective and error-free communication, demonstrate that a suitable warning chatbot does not necessarily require complex language processing capabilities. Additionally, our findings facilitate further research on accessibility via conversational design in the realm of crisis warnings.…”
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