A pathway from fragmentation to interoperability through standards-based enterprise architecture to enhance patient safety by Zoie Shui-Yee Wong, Yang Gong, Shin Ushiro

“…Abstract Creating an ontology is the essential step in natural language processing (NLP). To improve patient safety in this era of generative AI, it is crucial to develop a standards-driven, ontology-based architecture for patient safety that can seamlessly integrate with health systems, thereby facilitating effective detection and monitoring potentially preventable harms in healthcare. …”
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Benchmark for Evaluation of Danish Clinical Word Embeddings by Martin Sundahl Laursen, Jannik Skyttegaard Pedersen, Pernille Just Vinholt, Rasmus Søgaard Hansen, Thiusius Rajeeth Savarimuthu

“… In natural language processing, benchmarks are used to track progress and identify useful models. …”
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An XML Approach of Coding a Morphological Database for Arabic Language by Mourad Gridach, Noureddine Chenfour

“…Optimizing the production, maintenance, and extension of morphological database is one of the crucial aspects impacting natural language processing (NLP). For Arabic language, producing a morphological database is not an easy task, because this it has some particularities such as the phenomena of agglutination and a lot of morphological ambiguity phenomenon. …”
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Emotional State Analysis Model of Humanoid Robot in Human-Computer Interaction Process by Boxin Peng

“…In affective state analysis language processing, language coding, feature analysis, and Word2vec research are carried out. …”
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Atypical early neural responses to native and non-native language in infants at high likelihood for developing autism by Lauren Wagner, Megan Banchik, Tawny Tsang, Nana J. Okada, Rebecca Altshuler, Nicole McDonald, Susan Y. Bookheimer, Shafali S. Jeste, Shulamite Green, Mirella Dapretto

“…Whole-brain and a priori region-of-interest analyses were conducted to evaluate neural differences in language processing based on likelihood group and language condition. …”
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Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders by Muhammad Sajid, Kaleem Razzaq Malik, Ateeq Ur Rehman, Tauqeer Safdar Malik, Masoud Alajmi, Ali Haider Khan, Amir Haider, Seada Hussen

“…Abstract Although the Transformer architecture has established itself as the industry standard for jobs involving natural language processing, it still has few uses in computer vision. …”
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Negative symptoms in schizophrenia: a study in a large clinical sample of patients using a novel automated method by Robert Stewart, Hitesh Shetty, Matthew Broadbent, Angus Roberts, Rashmi Patel, Philip McGuire, Richard D Hayes, Nishamali Jayatilleke, Genevieve Gorrell, Chin-Kuo Chang, Richard Jackson, Nadia Foskett, Caroline Johnston

“…Objectives To identify negative symptoms in the clinical records of a large sample of patients with schizophrenia using natural language processing and assess their relationship with clinical outcomes.Design Observational study using an anonymised electronic health record case register.Setting South London and Maudsley NHS Trust (SLaM), a large provider of inpatient and community mental healthcare in the UK.Participants 7678 patients with schizophrenia receiving care during 2011.Main outcome measures Hospital admission, readmission and duration of admission.Results 10 different negative symptoms were ascertained with precision statistics above 0.80. 41% of patients had 2 or more negative symptoms. …”
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Dynamic Modeling and Analysis of Micro-Video Teaching System Based on Cloud Computing in College English Teaching by Ying Chen

“…The algorithm is composed of dynamic rule algorithm, language processing technology, and regular expression. …”
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A dataset dedicated to the training of large- language models for agronomic management practices and production in Norwegian agricultureGithubKaggle by Olena Bugaiova, Kristian Nikolai Jæger Hansen

“…The cleaned text data is valuable for training or evaluating Natural Language Processing (NLP) Models in an experimental context in Norway or adapting Large-Language Models (LLM) to the domain of Norwegian agriculture within the Norwegian language.…”
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Special Issue in Artificial Intelligence by Dora Maria Ballesteros

“…Artificial Intelligence applications include prediction, recommendation, classification and recognition, object detection, natural language processing, autonomous systems, among others. The topics of the articles in this special issue include deep learning applied to medicine [1, 3], support vector machine applied to ecosystems [2], human-robot interaction [4], clustering in the identification of anomalous patterns in communication networks [5], expert systems for the simulation of natural disaster scenarios [6], real-time algorithms of artificial intelligence [7] and big data analytics for natural disasters [8]. …”
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Resources for assigning MeSH IDs to Japanese medical terms by Yuka Tateisi

“…Medical Subject Headings (MeSH), a medical thesaurus created by the National Library of Medicine (NLM), is a useful resource for natural language processing (NLP). In this article, the current status of the Japanese version of Medical Subject Headings (MeSH) is reviewed. …”
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A Survey on Hardware Accelerators for Large Language Models by Christoforos Kachris

“…Large language models (LLMs) have emerged as powerful tools for natural language processing tasks, revolutionizing the field with their ability to understand and generate human-like text. …”
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Artificial Intelligence–Powered Training Database for Clinical Thinking: App Development Study by Heng Wang, Danni Zheng, Mengying Wang, Hong Ji, Jiangli Han, Yan Wang, Ning Shen, Jie Qiao

“…Case extraction was performed at a hospital’s case data center, and the best-matching cases were differentiated through natural language processing, word segmentation, synonym conversion, and sorting. …”
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Large Language Model Approach for Zero-Shot Information Extraction and Clustering of Japanese Radiology Reports: Algorithm Development and Validation by Yosuke Yamagishi, Yuta Nakamura, Shouhei Hanaoka, Osamu Abe

“… Abstract BackgroundThe application of natural language processing in medicine has increased significantly, including tasks such as information extraction and classification. …”
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COVID-19 Infodemic in Malaysia: Conceptualizing Fake News for Detection by Chee Kuan Lim, Zurinahni Zainol, Bahiyah Omar, Noor Farizah Ibrahim

“…Under the study of COVID-19 fake news detection, the synthetic minority oversampling technique (SMOTE) is used to generate synthetic instances of real news in the training set after natural language processing (NLP) and before data modelling because the number of fake news is approximately three times greater than that of real news. …”
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LEXCONN: A French Lexicon of Discourse Connectives by Charlotte Roze, Laurence Danlos, Philippe Muller

“…While a lexicon of discourse connectives associated with the relations they express can be very useful for researchers, especially in Natural Language Processing, few projects aim at collecting them exhaustively, and only in a small number of languages. …”
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Klasifikasi Laporan Keluhan Pelayanan Publik Berdasarkan Instansi Menggunakan Metode LDA-SVM by Muhammad Alkaff, Andreyan Rizky Baskara, Irham Maulani

“…Therefore, we need a solution that can automatically determine the report's context using Natural Language Processing techniques. This study aims to build automatic report classifications based on report topics addressed to authorized agencies by combining Latent Dirichlet Allocation (LDA) and Support Vector Machine (SVM). …”
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Teknik Identifikasi Fitur Berdasarkan Kalimat Pernyataan Kebutuhan dalam Konteks Pengembangan Software Product Line by M Syauqi Haris, Tri Astoto Kurniawan

“…The pattern of writing a requirement sentence with boilerplate requirements is used as the basis for automatically identifying software features using natural language processing (NLP) tools. In this research, 4 (four) dependency parser rules are proposed, which is one of the pipelines in NLP. …”
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Co-producing a safe mobility and falls informatics platform to drive meaningful quality improvement in the hospital setting: a mixed-methods protocol for the insightFall study by Ben Glampson, Clare Leon-Villapalos, Erik Mayer, Rachael Lear, Phoebe Averill, Catalina Carenzo, Rachel Tao, Robert Latchford

“…Based on these initial insights and further consultation with lay partners and clinical staff, a final data extraction template will be agreed. Natural language processing pipelines will be co-produced, clinically validated and integrated with QlikView. …”
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RespiroDynamics: A Multifaceted Dataset for Enhanced Lung Health Assessment Using Deep Learning by Ahmed Sharshar, Muhammad Sharshar, Hosam Elhady, Ahmed Aboeitta, Youssef Nafea, Yasser Ashraf, Mohammad Yaqub, Mohsen Guizani

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