Relationship Between Landscape Character and Public Preferences in Urban Landscapes: A Case Study from the East–West Mountain Region in Wuhan, China by Xingyuan Li, Wenqing Pang, Lizhi Han, Yufan Yan, Xianjie Pan, Diechuan Yang

“…Subsequently, we employ emotion analysis based on Natural Language Processing (NLP) techniques to analyze user-generated content (UGC) from Weibo check-in data to establish perception characteristic indicators reflecting public preferences. …”
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Continuing education for the prevention of mild cognitive impairment and Alzheimer’s-type dementia: a systematic review and overview of systematic reviews by Nina Matyas, Filiz Keser Aschenberger, Gernot Wagner, Stefanie Auer, Christoph Gisinger, Monika Kil, Irma Klerings

“…Based on 459 participants, preliminary data of the ongoing cohort study indicated that cognitive reserve statistically significantly increased in persons attending university classes compared with the control group (92.5% vs 55.7%, p<0.01). Likewise, language processing capacities statistically significantly improved (p<0.01). …”
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AI Discernment in Foot and Ankle Surgery Research: A Survey Investigation by Steven R. Cooperman DPM, MBA, AACFAS, Abisola Olaniyan MBBS, MPH, PhD, Roberto Brandao DPM, FACFAS

“…Trained on vast datasets, LLMs utilize machine learning and natural language processing to generate coherent responses. However, their use in scientific and medical research raises concerns about plagiarism and accuracy. …”
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A novel dual embedding few-shot learning approach for classifying bone loss using orthopantomogram radiographic notes by Pradeep Kumar Yadalam, Amit Rajabhau Pawar, Prabhu Manickam Natarajan, Carlos M. Ardila

“…Radiographic notes, which summarize clinical observations and preliminary interpretations, can be utilized for classification through natural language processing techniques, including Transformer-based models. …”
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AI in Medical Questionnaires: Innovations, Diagnosis, and Implications by Xuexing Luo, Yiyuan Li, Jing Xu, Zhong Zheng, Fangtian Ying, Guanghui Huang

“…In questionnaire development, natural language processing using generative models such as ChatGPT was used to construct culturally competent scales. …”
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Artificial intelligence in healthcare: transforming patient safety with intelligent systems—A systematic review by Francesco De Micco, Francesco De Micco, Gianmarco Di Palma, Gianmarco Di Palma, Davide Ferorelli, Anna De Benedictis, Anna De Benedictis, Luca Tomassini, Vittoradolfo Tambone, Mariano Cingolani, Roberto Scendoni, Roberto Scendoni

“…We utilized the online tool Rayyan for efficient screening and selection of relevant studies from three different online bibliographic.ResultsAI systems, including machine learning and natural language processing, show promise in detecting adverse events, predicting medication errors, assessing fall risks, and preventing pressure injuries. …”
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Enhancing Pulmonary Disease Prediction Using Large Language Models With Feature Summarization and Hybrid Retrieval-Augmented Generation: Multicenter Methodological Study Based on R... by Ronghao Li, Shuai Mao, Congmin Zhu, Yingliang Yang, Chunting Tan, Li Li, Xiangdong Mu, Honglei Liu, Yuqing Yang

“… Abstract BackgroundThe rapid advancements in natural language processing, particularly the development of large language models (LLMs), have opened new avenues for managing complex clinical text data. …”
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Generating dermatopathology reports from gigapixel whole slide images with HistoGPT by Manuel Tran, Paul Schmidle, Ruifeng Ray Guo, Sophia J. Wagner, Valentin Koch, Valerio Lupperger, Brenna Novotny, Dennis H. Murphree, Heather D. Hardway, Marina D’Amato, Judith Lefkes, Daan J. Geijs, Annette Feuchtinger, Alexander Böhner, Robert Kaczmarczyk, Tilo Biedermann, Avital L. Amir, Antien L. Mooyaart, Francesco Ciompi, Geert Litjens, Chen Wang, Nneka I. Comfere, Kilian Eyerich, Stephan A. Braun, Carsten Marr, Tingying Peng

“…The generated reports match the quality of human-written reports for common and homogeneous malignancies, as confirmed by natural language processing metrics and domain expert analysis. …”
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Improved Hypernymy Detection Algorithm Based on Heterogeneous Graph Neural Network by Li Ren, Jing Huang, Hai-Tao Jia, Shu-Bao Sun, Kai-Shi Wang, Yi-Le Wu

“…The detection of hyponymy–hypernymy semantic relations is an important task in the field of natural language processing, crucial to many downstream tasks such as information extraction, automatic reasoning, and personalized recommendations. …”
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Data Fusion of Medical Records and Clinical Data to Enhance Tuberculosis Diagnosis in Resource-Limited Settings by Alvaro D. Orjuela-Cañón, Andrés F. Romero-Gómez, Andres L. Jutinico, Carlos E. Awad, Erika Vergara, Maria A. Palencia

“…This paper explores the use of natural language processing (NLP) techniques and machine learning (ML) models to facilitate TB diagnosis in settings where robust data infrastructure is unavailable. …”
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Association Between COVID-19 During Pregnancy and Preterm Birth by Trimester of Infection: Retrospective Cohort Study Using Large-Scale Social Media Data by Ari Z Klein, Shriya Kunatharaju, Su Golder, Lisa D Levine, Jane C Figueiredo, Graciela Gonzalez-Hernandez

“…MethodsIn this retrospective cohort study, we used natural language processing and machine learning, followed by manual validation, to identify self-reports of pregnancy on Twitter and to search these users’ collection of publicly available tweets for self-reports of COVID-19 infection during pregnancy and, subsequently, a preterm birth or term birth outcome. …”
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ECG-LM: Understanding Electrocardiogram with a Large Language Model by Kai Yang, Massimo Hong, Jiahuan Zhang, Yizhen Luo, Suyuan Zhao, Ou Zhang, Xiaomao Yu, Jiawen Zhou, Liuqing Yang, Ping Zhang, Mu Qiao, Zaiqing Nie

“…Methods: Although recent advancements in multi-modal large language modeling have propelled their application scope beyond the natural language processing domain, their applicability to ECG processing remains largely unexplored, partly due to the lack of text–ECG data. …”
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Leveraging ChatGPT for Enhancing Arabic NLP: Application for Semantic Role Labeling and Cross-Lingual Annotation Projection by Ferial Senator, Abdelaziz Lakhfif, Imene Zenbout, Hanane Boutouta, Chahrazed Mediani

“…In this paper, we leverage ChatGPT for two main sub-tasks in Arabic language processing. <xref ref-type="disp-formula" rid="deqn1">(1)</xref> Creating an Arabic annotated resource with emotional semantic roles from an English corpus, using cross-lingual annotation projection approach. …”
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Role of AI in empowering and redefining the oncology care landscape: perspective from a developing nation by Isha Goel, Isha Goel, Yogendra Bhaskar, Nand Kumar, Sunil Singh, Mohammed Amanullah, Ruby Dhar, Subhradip Karmakar

“…Artificial Intelligence (AI), driven by advancements in machine learning, deep learning, and natural language processing, can profoundly transform the underlying shortcomings in the healthcare industry, more for populous nations like India. …”
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Automatic Identification of Amharic Text Idiomatic Expressions Using a Deep Learning Approach by Habtamu Hunegnaw Limenih, Abebe Belay Adege, Abrham Yaregal Alene, Habtamu Tariku Demasu, Habtamu Molla Belachew

“…Natural Language Processing (NLP) is a tract of artificial intelligence and linguistics devoted to making computers understand the statements or words written in human languages. …”
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Harnessing Moderate-Sized Language Models for Reliable Patient Data Deidentification in Emergency Department Records: Algorithm Development, Validation, and Implementation Study by Océane Dorémus, Dylan Russon, Benjamin Contrand, Ariel Guerra-Adames, Marta Avalos-Fernandez, Cédric Gil-Jardiné, Emmanuel Lagarde

“…Evaluation focused on PII-level (recall, precision, and F1 ResultsThe generative model Mistral 7B performed the highest with an overall F1 ConclusionsOur research underscores the significant capabilities of generative natural language processing models, with Mistral 7B standing out for its superior ability to deidentify clinical texts efficiently. …”
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Applying AI to Structured Real-World Data for Pharmacovigilance Purposes: Scoping Review by Stella Dimitsaki, Pantelis Natsiavas, Marie-Christine Jaulent

“…There are several instances of AI approaches applied to RWD; however, most studies focus on unstructured RWD (conducting natural language processing on various data sources, eg, clinical notes, social media, and blogs). …”
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AI-based thematic exploration to understand patients with myasthenia gravis by serological subtype by Louis Jackson, Caroline Brethenoux, Alyssa DeLuca, Jacqueline Pesa, Zia Choudhry, Patrick Furey, Rosario Alvarez, Laura Gonzalez, Alex Lorenzo, Raghav Govindarajan, Ashley E. L. Anderson

“…Advanced search techniques and AI-powered algorithms were used to extract/organize data by topics into a large, unstructured dataset. Natural language processing identified frequent topics, sentiments, mindsets, and drivers/barriers to treatment.ResultsIn total, 8,784 conversations were mined from seropositive patients and/or their caregivers (including 1,058 AChR+, 589 MuSK+, and 537 LRP4+) and 2,261 were mined from seronegative patients and/or their caregivers. …”
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Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study by Denise Lee, Akhil Vaid, Kartikeya M Menon, Robert Freeman, David S Matteson, Michael L Marin, Girish N Nadkarni

“… Abstract BackgroundPopularized by ChatGPT, large language models (LLMs) are poised to transform the scalability of clinical natural language processing (NLP) downstream tasks such as medical question answering (MQA) and automated data extraction from clinical narrative reports. …”
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Spatio-Temporal Patterns and Sentiment Analysis of Ting, Tai, Lou, and Ge Ancient Chinese Architecture Buildings by Jinghan Xie, Jinghang Wu, Zhongyong Xiao

“…., Standard deviation ellipse and Geographic detector), Word cloud generation, and sentiment analysis, which uses Natural Language Processing techniques to identify subjective emotions in text, were applied to investigated the research issues. …”
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