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  1. 14601

    A meta-analysis for the nighttime light remote sensing data applied in urban research: Key topics, hotspot study areas and new trends by Baiyu Dong, Ruyi Zhang, Sinan Li, Yang Ye, Chenhao Huang

    Published 2025-06-01
    “…Nighttime light (NTL) data have become an essential tool for urban remote-sensing research in the past 25 years because of its ability to intuitively detect human activities. …”
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    Article
  2. 14602

    Multi-century mean summer temperature variations in the Southern Rhaetian Alps reconstructed from <i>Larix decidua</i> blue intensity data by R. Cerrato, M. C. Salvatore, M. C. Salvatore, M. Brunetti, A. Somma, C. Baroni, C. Baroni

    Published 2025-03-01
    “…The results from this investigation will extend the current knowledge on the applicability of using BI data to study the European larch, and the reconstruction described herein is the first attempt to determine whether this proxy can be used for dendroclimatic aims. …”
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  3. 14603

    Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study by Chanmin Park, Changho Han, Su Kyeong Jang, Hyungjun Kim, Sora Kim, Byung Hee Kang, Kyoungwon Jung, Dukyong Yoon

    Published 2025-04-01
    “…ObjectiveWe aimed to create a novel machine learning model for delirium prediction in ICU patients using only continuous physiological data. MethodsWe developed models integrating routinely available clinical data, such as age, sex, and patient monitoring device outputs, to ensure practicality and adaptability in diverse clinical settings. …”
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  4. 14604
  5. 14605

    Peat oxic and anoxic controls of <i>Sphagnum</i> decomposition rates in the Holocene Peatland Model decomposition module estimated from litterbag data by H. Teickner, H. Teickner, E. Pebesma, K.-H. Knorr

    Published 2025-06-01
    “…<p>The Holocene Peatland Model (HPM) is a widely applied model for understanding and predicting long-term peat accumulation, but it is difficult to test due to its complexity, measurement errors, and lack of data. Instead of testing the complete model, tests of individual modules may avoid some of these problems. …”
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    Article
  6. 14606
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  8. 14608

    Análisis de habilidades y percepciones sobre mHealth en el manejo de pacientes crónicos por profesionales de atención primaria by Daniel Monasor Ortola, José Joaquín Mira Solves, Antonio Esteve Ríos

    Published 2025-02-01
    “…Measurements: Participants completed an anonymized ad hoc questionnaire divided into two sections: sociodemographic data and questions regarding the use of mobile health technologies and the internet. …”
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  9. 14609
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  11. 14611

    The Unfolding Analysis for Symbolic Objects Based on the Example of the External Car Advertisement Evaluation by Artur Zaborski, Marcin Pełka

    Published 2024-03-01
    “…Results: The empirical part presents an application for unfolding symbolic data to evaluate customers’ preferences, where car advertisements are used as the example. …”
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    Article
  12. 14612

    Deep learning identification of reward-related neural substrates of preadolescent irritability: A novel 3D CNN application for fMRI by Johanna C. Walker, Conner Swineford, Krupali R. Patel, Lea R. Dougherty, Jillian Lee Wiggins

    Published 2025-06-01
    “…Irritability, defined as a lowered threshold for angry responses to blocked rewards, is a promising neurodevelopmental marker for mental health risk due to its robust, transdiagnostic predictive power in youth. In this study, data from the Adolescent Brain and Cognitive Development (ABCD) baseline sample (N = 6065) were utilized for a novel application of a 3D CNN to whole-brain fMRI data acquired during the reward anticipation period of the monetary incentive delay task to predict parent-reported youth irritability severity, measured dimensionally. …”
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  13. 14613

    Conceptual framework for data harmonisation in mental health using the International Classification of Functioning, Disability and Health: an example with the R2D2-MH consortium by Louise Gallagher, Tony Charman, Dieter Wolke, Jan Buitelaar, Sven Bölte, Emily Jones, Thomas Bourgeron, Marie Schaer, Kristien Hens, Declan Murphy, Melissa H Black, Christine Ecker, Yair Sadaka, Beate St Pourcain, Stef Bonnot-Briey

    Published 2024-12-01
    “…Although the linking process necessarily entails an element of subjectivity, the application of established rules can increase rigour and transparency of the harmonisation process.Conclusions We present the first steps towards data harmonisation in mental health that is compatible with contemporary approaches in psychiatry, being more capable of capturing diversity and aligning with more transdiagnostic and neurodiversity-affirmative ways of understanding data.Clinical implications Our findings show promise, but future work is needed to address quantitative harmonisation. …”
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  14. 14614
  15. 14615

    Application Of ArtifiCial Intelligence in E-Governance: A Comparative Study of Supervised Machine Learning and Ensemble Learning Algorithms on Crime Prediction. by Niyonzima, Ivan, Muhaise, Hussein, Akankwasa, Aureri

    Published 2024
    “…Therefore, this study proposes the application of supervised machine learning techniques in the prediction of crimes basing on the past crime data. …”
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  16. 14616

    Determination and Application of Critical Control Points on Ebi Fry Production (Value Added Product) at PT. Jala Sembilan Semarang, Central Java by Revanda Rizky Putraisya, Juni Triastuti

    Published 2022-09-01
    “…The working method used is a descriptive method with data collection including primary data and secondary data. …”
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  17. 14617

    Federated Learning Based on an Internet of Medical Things Framework for a Secure Brain Tumor Diagnostic System: A Capsule Networks Application by Roman Rodriguez-Aguilar, Jose-Antonio Marmolejo-Saucedo, Utku Köse

    Published 2025-07-01
    “…Federated learning has been successfully applied in medical settings, including diagnostic applications involving medical images such as MRI data. …”
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    Article
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