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    Leveraging Deep Learning and Multimodal Large Language Models for Near-Miss Detection Using Crowdsourced Videos by Shadi Jaradat, Mohammed Elhenawy, Huthaifa I. Ashqar, Alexander Paz, Richi Nayak

    Published 2025-01-01
    “…This study introduces a novel AI-based framework designed to detect and analyze near-miss and crash events in crowdsourced dashcam footage. …”
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    Professional Barriers in Energy Efficiency Retrofits—A Solution Based on Information Flow Modeling by Xilong Liao, Chun Wang, Baiyi Li, Baizhan Li, Chenqiu Du

    Published 2025-01-01
    “…It is proposed that improved information integration and collaboration under this framework will significantly promote the advancement of professional generative AI.…”
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  11. 2991

    Comparative Outcomes of Meropenem–Vaborbactam vs. Ceftazidime–Avibactam Among Adults Hospitalized with an Infectious Syndrome in the US, 2019–2021 by Marya D. Zilberberg, Brian H. Nathanson, Mark A. Redell, Kate Sulham, Andrew F. Shorr

    Published 2025-01-01
    “…CZA, we conducted a multicenter retrospective cohort study of all adult hospitalized patients with a serious infection (sepsis, urinary tract infection [UTI], complicated intraabdominal [cIAI] infection, or pneumonia) within the PINC AI Database, 2019–2021. Descriptive statistics compared the two groups along demographic and clinical characteristics, and multiple regression derived adjusted outcomes. …”
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    Comparative analysis of deep learning models for crack detection in buildings by S. Siva Rama Krishnan, M. K. Nalla Karuppan, Adil O. Khadidos, Alaa O. Khadidos, Shitharth Selvarajan, Saarthak Tandon, Balamurugan Balusamy

    Published 2025-01-01
    “…The development of Artificial Intelligence (AI) techniques, provide favourable solutions in-order to handle, manage and solve building cracks, through analysis using deep image neural network models, that perform classification of the building with crack images. …”
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    Artificial intelligence methods applied to longitudinal data from electronic health records for prediction of cancer: a scoping review by Victoria Moglia, Owen Johnson, Gordon Cook, Marc de Kamps, Lesley Smith

    Published 2025-01-01
    “…Artificial intelligence (AI) models have shown promise in the early detection and diagnosis of cancer, but there is limited evidence on methods that fully exploit the longitudinal data stored within electronic health records (EHRs). …”
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