Showing 1 - 20 results of 1,503 for search 'missing integration', query time: 0.10s Refine Results
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    Health promotion actions and maternal near miss: an integrative review by Lívia Mara de Araújo, Maria Evilene Macena de Almeida, Ana Kelve de Castro Damasceno, Camila Teixeira Moreira Vasconcelos, Régia Christina Moura Barbosa Castro

    Published 2021-01-01
    “… Objective: to identify health promotion actions to reduce maternal near misses. Methods: this is an integrative review of the literature. …”
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    Health promotion actions and maternal near miss: an integrative review by Lívia Mara de Araújo, Maria Evilene Macena de Almeida, Ana Kelve de Castro Damasceno, Camila Teixeira Moreira Vasconcelos, Régia Christina Moura Barbosa Castro

    Published 2021-01-01
    “… Objective: to identify health promotion actions to reduce maternal near misses. Methods: this is an integrative review of the literature. …”
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    Article
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    Fatores de risco para near miss materno: revisão integrativa [Risk factors for maternal near miss: an integrative review] [Factores de riesgo para near miss materno: revisión integrativa] by Aline Amorim da Silveira, Ana Paula de Assis Sales, Andreia Insabralde de Queiroz Cardoso

    Published 2022-10-01
    “…Objective: to summarize the main risk factors for maternal near miss. Method: this integrative literature review was performed on March 21, 2021, in the following databases: the National Library of Medicine – Medline via PubMed, the Cumulative Index to Nursing and Allied Health Literature, Science Direct, Elsevier’s Scopus, Web of Science, and the Virtual Health Library portal. …”
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    Synergy-CLIP: Extending CLIP With Multi-Modal Integration for Robust Representation Learning by Sangyeon Cho, Jangyeong Jeon, Mingi Kim, Junyeong Kim

    Published 2025-01-01
    “…Multi-modal representation learning has become a pivotal area in artificial intelligence, enabling the integration of diverse modalities such as vision, text, and audio to solve complex problems. …”
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    Filling in missing puzzle pieces in protein structural biology with cross-linking mass spectrometry by Zheng Ser

    Published 2025-01-01
    “…In this perspective, I sketch out several ways that cross-linking mass spectrometry can contribute to filling in some of these missing pieces: Identification of cross-linked interactions in highly flexible protein regions not captured by other structural techniques; capturing conformational changes of protein complexes in different functional states; serving as distance constraints in integrative structural modelling and providing structural information of in cellulo proteins. …”
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    Enhancing landslide dam stability prediction: a data-driven framework integrating missing data imputation and optimal threshold discrimination by Xiaojun Li, Xiaobo Zhang, Jun He, Yixiang Song, Yanqi Li

    Published 2025-07-01
    “…IntroductionAccurate prediction of landslide dam stability is critical for mitigating downstream hazards, but reliable models are hindered by incomplete inventories due to missing data. This study addresses this gap by integrating advanced imputation techniques with machine learning (ML) to enhance prediction accuracy and applicability.MethodsWe compiled a global inventory of 518 landslide dam cases (25% missing data rate) and evaluated five imputation methods: generative adversarial imputation nets (GAIN), missForest, multiple imputations by chained equations (MICE), K-nearest neighbors (KNN), and mean most-frequency (MMF). …”
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    Analytical model of the ADS-B information integrity radar monitoring by V. L. Kuznetsov, V. V. Dupikov

    Published 2016-11-01
    Subjects: “…ads-b information integrity…”
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    Integrating Prescriptive Analytics, XAI, and Missing Data Handling into a Trust-centric Ensemble Model for Persuasive Interventions: A Scoping Review in Higher Education by Matipa Ricky Ngandu, Gardner Mwansa, Colin Chibaya

    Published 2025-06-01
    “…This scoping review explores the potential of integrating prescriptive analytics, eXplainable AI, and missing data handling techniques into a trust-centric ensemble model to enhance the persuasiveness of optimised actionable insights. …”
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